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Marijuana 

and the 

Cannabinoids 



Edited by 

Mahmoud A. ElSohly, PhD 




Humana Press 



Marijuana and the Cannabinoids 



FORENSIC 



SCIENCE and MEDICINE 



Steven B. Karch, md, SERIES EDITOR 

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Marijuana and 
the cannabinoids 



Edited by 

Mahmoud A. ElSohly, PhD 

The School of Pharmacy, The University of Mississippi; 
ElSohly Laboratories Inc., Oxford, MS 



Humana Press 




Totowa, New Jersey 



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Library of Congress Cataloging-in-Publication Data 

Marijuana and the cannabinoids / edited by Mahmoud A. ElSohly. 
p. ; cm. — (Forensic science and medicine) 
Includes bibliographical references and index. 
ISBN 1-58829-456-0 (alk. paper) 
1. Cannabinoids. I. ElSohly, Mahmoud A. II. Series. 
[DNLM: 1. Cannabinoids. 2. Cannabis. QV 77.7 M335 15 2006] 
QP801.C27M355 2006 
615'.7827-dc22 

2006012285 



Preface 



Although primarily used today as one of the most prevalent illicit leisure drugs, 
the use of Cannabis sativa L., commonly referred to as marijuana, for medicinal 
purposes has been reported for more than 5000 years. Marijuana use has been shown 
to create numerous health problems, and, consequently, the expanding use beyond 
medical purposes into recreational use (abuse) resulted in control of the drug through 
international treaties. 

Much research has been carried out over the past few decades following the 
identification of the chemical structure of THC in 1964. The purpose of Marijuana 
and the Cannabinoids is to present in a single volume the comprehensive knowledge 
and experience of renowned researchers and scientists. Each chapter is written 
independently by an expert in his/her field of endeavor, ranging from the botany, the 
constituents, the chemistry and pharmacokinetics, the effects and consequences of 
illicit use on the human body, to the therapeutic potential of the cannabinoids. 

MahmoudA. ElSohly, pud 



v 



Contents 



Preface v 

Contributors ix 

Chapter 1 

Cannabis and Natural Cannabis Medicines 

Robert C. Clarke and David P. Watson 1 

Chapter 2 

Chemistry and Analysis of Phytocannabinoids 
and Other Cannabis Constituents 

Rudolf Brenneisen 17 

Chapter 3 

Chemical Fingerprinting of Cannabis as a Means of Source Identification 

Mahmoud A. ElSohly, Donald F. Stanford, 

and Timothy P. Murphy 57 

Chapter 4 

Marijuana Smoke Condensate: Chemistry and Pharmacology 

Hala N. ElSohly and Mahmoud A. ElSohly 67 

Chapter 5 

Pharmacology of Cannabinoids 

Lionel P. Raymon and H. Chip Walls 97 

Chapter 6 

The Endocannabinoid System and the Therapeutic Potential 
of Cannabinoids 

Billy R. Martin 125 



vii 



viii Contents 

Chapter 7 

Immunoassays for the Detection of Cannabis Abuse: 

Technologies, Development Strategies, and Multilevel Applications 

Jane S-C. Tsai 145 

Chapter 8 

Mass Spectrometric Methods for Determination 
of Cannabinoids in Physiological Specimens 

Rodger L. Foltz 179 

Chapter 9 

Human Cannabinoid Pharmacokinetics and Interpretation 

of Cannabinoid Concentrations in Biological Fluids and Tissues 

Marilyn A. Huestis and Michael L. Smith 205 

Chapter 10 

Medical and Health Consequences of Marijuana 

Jag H. Khalsa 237 

Chapter 11 

Effects of Marijuana on the Lung and Immune Defenses 

Donald P. Tashkin and Michael D. Roth 253 

Chapter 12 

Marijuana and Driving Impairment 

Barry K. Logan 277 

Chapter 13 

Postmortem Considerations 

Steven B. Karch 295 

Chapter 14 

Cannabinoid Effects on Biopsychological, Neuropsychiatric, 
and Neurological Processes 

Richard E. Musty 303 

Index 317 



Contributors 



Rudolf Brenneisen, PhD • Department of Clinical Research, Laboratory 

for Phytopharmacology, Bioanalytics and Pharmacokinetics, University of Bern, 
Bern, Switzerland 

Robert C. Clarke, ba • International Hemp Association, Amsterdam, The Netherlands 

Hala N. ElSohly, PhD • National Center for Natural Products Research, Research 
Institute of Pharmaceutical Sciences, The School of Pharmacy, The University 
of Mississippi, Oxford, MS 

Mahmoud A. ElSohly, PhD • National Center for Natural Products Research, Research 
Institute of Pharmaceutical Sciences, The School of Pharmacy, The University 
of Mississippi; ElSohly Laboratories Inc., Oxford, MS 

Rodger L. Foltz, PhD • Center for Human Toxicology, University of Utah, Salt Lake 
City, UT 

Marilyn A. Huestis, PhD • Chemistry and Drug Metabolism, Intramural Research 
Program, National Institute on Drug Abuse, National Institutes of Health, 
Baltimore, MD 

Steven B. Karch, md • Consultant Pathologist/Toxicologist, Berkeley, CA 

Jag H. Khalsa, PhD • Chief, Medical Consequences Branch, Division 

of Pharmacotherapies and Medical Consequences of Drug Abuse (DPMCDA), 
National Institute on Drug Abuse, Bethesda, MD 

Barry K. Logan, PhD • Washington State Toxicologist and Director of Forensic 
Laboratory Services Bureau, Washington State Patrol, Seattle, WA 

Billy R. Martin, PhD • Louis and Ruth Harris Professor and Chair, Department 
of Pharmacology and Toxicology, Virginia Commonwealth University, 
Richmond, VA 

Timothy P. Murphy, ba • ElSohly Laboratories Inc., Oxford, MS 

Richard E. Musty, PhD • Department of Psychology, University of Vermont, 
Burlington, VT 

Lionel P. Raymon, PharmD, PhD • Kaplan Medical, Pharmacology Chair and Department 
of Pathology, Miller School of Medicine, University of Miami, Miami, FL 

Michael D. Roth, md • Professor of Medicine, Division of Pulmonary and Critical 
Care, Department of Medicine, David Geffen School of Medicine, University 
of California at Los Angeles, Los Angeles, CA 



ix 



X 



Contributors 



Michael L. Smith, PhD, dabft • Division of Forensic Toxicology, Office of the Armed 
Forces Medical Examiner, Rockville, MD 

Donald F Stanford, ms • National Center for Natural Products Research, Research 
Institute of Pharmaceutical Sciences, School of Pharmacy, The University 
of Mississippi, Oxford, MS 

Donald P. Tashkin, md • Professor of Medicine, Division of Pulmonary and Critical 
Care, Department of Medicine, David Geffen School of Medicine, University 
of California at Los Angeles, Los Angeles, CA 

Jane S-C. Tsai, PhD • Director, Research and Development, Roche Diagnostics, 
Indianapolis, IN 

H. Chip Walls, bs • Technical Director, Forensic Toxicology Laboratory, Miller School 
of Medicine, University of Miami, School of Medicine, Homestead, FL 

David P. Watson • CEO, HortaPharm BV, Amsterdam, The Netherlands 



Chapter 1 



Cannabis and Natural Cannabis 
Medicines 

Robert C. Clarke and David P. Watson 

1. Introduction 

Cannabis plants produce many compounds of possible medical importance. This 
chapter briefly explains the life cycle, origin, early evolution, and domestication of 
Cannabis, plus provides a brief history of drug Cannabis breeding and looks into the 
future of Cannabis as a source of medicines. Cannabis is among the very oldest of 
economic plants providing humans with fiber for spinning, weaving cloth, and mak- 
ing paper; seed for human foods and animal feeds; and aromatic resin containing com- 
pounds of recreational and medicinal value. Human selection for varying uses and 
natural selection pressures imposed by diverse introduced climates have resulted in a 
wide variety of growth forms and chemical compositions. Innovative classical breed- 
ing techniques have been used to improve recreational drug forms of Cannabis, result- 
ing in many cannabinoid-rich cultivars suitable for medical use. The biosynthesis of 
cannabinoid compounds is unique to Cannabis, and cultivars with specific chemical 
profiles are being developed for diverse industrial and pharmaceutical uses. 

2. Life Cycle and Ecology 

Cannabis is an annual crop plant propagated from seed and grows vigorously 
when provided an open sunny location with light well-drained soil, ample nutrients, 
and water. Cannabis can reach up to 5 m (16 ft.) in height in a 4- to 8-month spring-to- 
autumn growing season. Feral Cannabis populations are frequently found in associa- 
tion with human habitation. Disturbed lands such as active and disused farm fields, 
roadsides, railways, trails, trash piles, and exposed riverbanks are ideal habitats for 

From: Forensic Science and Medicine: Marijuana and the Cannabinoids 
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey 

/ 



2 



Watson and Clarke 



wild and feral Cannabis because they provide open niches exposed to adequate sun- 
light. 

Seeds usually germinate in 3-7 days. During the first 2-3 months of growth, 
juvenile plants respond to increasing day length with a more vigorous vegetative growth 
characterized by an increasing number of leaflets on each leaf. Later in the season 
(after the summer solstice), shorter days (actually longer nights) induce flowering and 
complete the life cycle. Cannabis begins to flower when exposed to short day lengths 
of 12-14 hours or less (long nights of 10-12 hours or more) depending on its latitude 
of origin. However, a single evening of interrupted darkness can disrupt flowering and 
delay maturation. Conversely, a day or two of short day length can induce flowering 
that may be irreversible in early-maturing varieties. If an individual plant grows with 
sufficient space, as in seed or resin production, flower-bearing limbs will grow from 
small growing points located at the base of the leaf petioles originating from nodes 
along the main stalk. The flowering period is characterized by leaves bearing decreas- 
ing numbers of leaflets and an accompanying change from vegetative growth and bio- 
mass accumulation to floral induction, fertilization, seed maturation, and resin 
production (1). 

Cannabis is normally dioecious (male and female flowers developing on sepa- 
rate plants), and the gender of each plant is anatomically indistinguishable before flow- 
ering. However, Mandolino and Ranalli (2) report success using random amplified 
polymorphic DNA analysis to identify male-specific DNA markers, and female-asso- 
ciated DNA polymorphisms were also described by Hong et al. (3). The floral devel- 
opment of male and female plants varies greatly. Whereas male flowers with five 
petals and prominent stamens hang in loose clusters along a relatively leafless upright 
branch, the inconspicuous female flowers are crowded into dense clusters along with 
small leaflets at the base of each larger leaf along the branch (see Fig. 1). Pollen grains 
require air currents to carry them to the female flowers, resulting in fertilization and 
consequent seed set. Viable pollen can be carried by the wind for considerable dis- 
tance (4); the male plants cease shedding pollen after 2-4 weeks and usually die before 
the seeds in the female plants ripen. Pollen has been frozen and successfully used for 
seed production up to 3 years later. 

The single seed in each female flower ripens in 3-8 weeks and will either be 
harvested, be eaten by birds or rodents, or fall to the ground, where they may germi- 
nate the following spring. This completes the natural 4- to 6-month life cycle. A large 
female plant can produce up to half a kilogram of seed. Cannabis seeds are a balanced 
source of essential fatty acids and easily digestible proteins and are suitable for use as 
whole foods and dietary supplements. Essential fatty acids have been shown to have 
many important physiological roles, and hemp seed oil is a valuable nutraceutical (5). 
Recent research has confirmed that topical application of hemp seed oil is effective in 
treating ear, nose, and throat ailments (6). 

3. Field Crop Production 

When industrial hemp crops are grown for fiber or seed, both male and female 
plants are usually left standing in the field until harvest. Most medical Cannabis is 
grown for its psychoactive resin by a different technique. In the early 1970s, a handful 



Cannabis and Natural Cannabis Medicines 



3 




Fig. 1. Medical Cannabis cultivars grown in the United Kingdom by GW Pharmaceu- 
ticals, which form the basis for CW's development of prescription medicines. The 
larger inflorescence (A) is a cannabidiol (CBD)-rich cultivar containing only traces of 
A 9 -tetrahydrocannabinol (THC), and the smaller inflorescence (B) is a THC-rich 
cultivar containing only traces of CBD. 



4 



Watson and Clarke 



of North American illicit marijuana cultivators began to grow sinsemilla (Spanish for 
"without seed") marijuana that within a few years became the predominant style of 
North American and European marijuana production. The sinsemilla effect is achieved 
by eliminating male plants from the fields, leaving only the unfertilized and therefore 
seedless female plants to mature for later flower and/or resin harvest.* In lieu of set- 
ting seed in the earliest flowers, the female plants continue to produce additional flowers 
covered by resin glands, which increases the percentage of psychoactive and medi- 
cally valuable A 9 -tetrahydrocannabinol (THC) or other cannabinoids in these flowers. 
Yields of terpenoid-rich essential oils produced in the resin glands along with the 
closely related terpenophenolic cannabinoids are also significantly raised in seedless 
flowers (7). Throughout the 1980s, the vast majority of domestically produced North 
American and European drug Cannabis was grown from seed in outdoor gardens, but 
during the 1990s the popularity of growing sinsemilla in greenhouses and indoors 
under artificial lights grew rapidly. 

4. Greenhouse and Grow Room Production 

Most Cannabis presently used for medical purposes is grown indoors under arti- 
ficial lights. Modern indoor growers most often grow their own clones under halide 
and sodium vapor light systems set up in attics, bedrooms, or basements. Crops grown 
from seed are typically made up of large male and female plants that require a lot of 
space and exhibit a wide range of physical and biochemical characteristics. A Can- 
nabis breeder relies on this variation as genetic potential for improving varieties, 
whereas a drug Cannabis producer wants a profitable and uniform crop and uses female 
clones to improve grow room yields. Consequently, vegetative production of female 
clones and the production of seedless flowers preclude the possibility of seed produc- 
tion and variety improvement. Vegetatively propagated crops are preferred because 
indoor garden space is limited, only female Cannabis plants produce resin of medical 
value, and it is both inconvenient and expensive to purchase reliable drug Cannabis 
seed. In addition, the legal systems of many nations penalize growers of more plants 
(vegetative, male or female) with harsher penalties. Under artificial growing condi- 
tions, crops are reproduced vegetatively by rooting cuttings of only select female plants, 
transplanting, and inducing flowering almost immediately so that the mature crop is 
short and compact. Cuttings of one plant are all genetically identical members of a 
single clone, so they will all respond in the same way to environmental influences and 
will be very similar in appearance. When environmental influences remain constant, 
the clone will yield serial crops of nearly identical uniform seedless females each time 
it is grown. 

Female "mother" plants used for cutting stock must be maintained in a constantly 
vegetative state under 18-hour or longer day lengths or they will begin to flower. 
Serial cuttings can be removed, rooted, grown under long day length, and used to 
replace older mother plants indefinitely. If the mother plants remain free of viruses or 
other pathogens, there is no loss of vigor after multiple rounds of vegetative propaga- 



*This technique was first encountered by British working in India, but we are unsure of its history prior 
to 1800. 



Cannabis and Natural Cannabis Medicines 



5 



tion. Serially propagated clones have been maintained for more than 20 years. When- 
ever flowering plants are required, small rooted cuttings (10-30 cm tall) are moved 
into a flowering room with a day length of 10-13 hours to mature in 7-14 weeks.* 

Vegetatively produced plants can fully mature when they are less than 1 m (3 ft.) 
tall and form flowers from top to bottom and look like a rooted branch from a large 
plant grown from seed. The length of time between the induction of flowering and full 
maturity of the female floral clusters depends largely on the variety being grown and 
the day length. Some cultivars mature much more quickly than others, and plants tend 
to be shorter when mature than those of slower-ripening varieties. Cannabis plants 
mature faster when they are given shorter day lengths of 10 hours, but most cultivars 
have an optimum day length requirement for maximum flower production in the shortest 
time — around 12-13 hours. Under ideal environmental conditions and expert man- 
agement, yields of dried flowers commonly reach 400 g/m 2 per crop cycle. As a result 
of multiple cropping four or five times per year, total annual yields can add up to more 
than 2 kg of dried flowers per square meter. 

In vitro techniques combined with low temperatures would allow long-term stor- 
age of wide varieties of living germplasm and could be an important storage technique 
for germplasm collections and breeders. Several research groups have reported suc- 
cess with vegetatively reproducing and initiating shooting in undifferentiated callus 
tissue and rooting of branch tips. The induction of rooting in callus and branch tips is 
straightforward. However, inducing shoots in callus tissue has proven more problem- 
atic and needs additional improvement (2,8). Further research and commercial appli- 
cations of in vitro techniques are expected in the near future. 

5. Resin Gland Anatomy and Development 

As resin gland development commences, the medically important cannabinoids 
and the associated terpenes begin to appear. Although the cannabinoids are odorless, 
terpenes are the primary aromatic principles found in the essential oil of Cannabis 
(9,10). Most interesting economically and medically are the cannabinoid-rich terpe- 
noid secretions of the head cells of glandular hairs densely distributed across the myriad 
surfaces of the female flowers. Male plants are of no consequence in medicine pro- 
duction because they develop few glandular trichomes and consequently produce few 
cannabinoids or terpenes. Solitary resin glands most often form at the tips of slender 
stalks that form as extensions of the plant surface and glisten in the light. The cluster 
of one to two dozen glandular head cells atop each stalk secretes aromatic terpene- 
containing resins with very high percentages of cannabinoids (>80%) that collects in 
vesicles under a thin membrane surrounding the secretory head cells. The secreted 
resin component is in large part physically segregated from the secretory cells (11). 
This isolates the resin from the atmosphere as well as membrane-bound enzyme sys- 
tems within the secretory cells, possibly protecting the terpenes and cannabinoids from 
oxidative degradation and enzymatic change. At the base of each cluster of resin head 



'"Cannabis breeders maintain male clones in the same way and induce them to flower whenever pollen 
is required to produce seed. However, males are often more difficult than females to maintain in the vegeta- 
tive state. 



6 



Watson and Clarke 




Fig. 2. Microscope photograph and drawing of a Cannabis resin gland. The secretory 
head cells are easily visible within the transparent blister of cannabinoid and terpe- 
noid-rich resin. (Photo courtesy of David Potter, drawing from ref. 14.) 



cells lies an abscission layer allowing the resin gland and secreted resin to be easily 
removed by mechanical means (see Fig. 2). Hashish or charas is simply millions of 
resin glands that have been rubbed, shaken, or washed from fresh or dry plants and 
compressed into a dense mass (11). 

Resin glands containing cannabinoids and terpenes may have an adaptive sig- 
nificance in reducing insect and fungal attack (12). However, Cannabis crops are sub- 
ject to infestation by a wide variety of pests (13), particularly under greenhouse and 
grow room conditions. 

6. Cannabinoid and Terpenoid Biosynthesis 

It is not surprising that cannabinoids are produced along with terpenoid com- 
pounds. Terpenes comprise a large group of compounds synthesized from C 10 isoprene 
subunits. Monoterpenes (C, ) and sesquiterpenes (C 15 ) are the classes most commonly 
found in Cannabis. Terpenoids are the primary aromatic constituents of Cannabis 
resin, although they constitute only a small percentage of organic solvent extracts. 
Cannabinoids are terpenophenolic compounds chemically related to the terpenoid com- 
pounds as the ring structure is derived from a geranyl pyrophosphate C 10 terpenoid 
subunit. Cannabinoids make up a large portion of the resin and can make up as much 
as 30% by weight of dried flowering tops. Cannabinoids are not significantly present 
in extracts prepared by steam distillation (15). 



Cannabis and Natural Cannabis Medicines 



7 



Our basic understanding of the biosynthesis of the major cannabinoids comes 
largely from the research of Yukihiro Shoyama and colleagues at Kyushu University 
in Japan (16,17). Cannabinoid biosynthesis begins with the incorporation of geranyl 
pyrophosphate (a terpenoid compound) with either a C,„ polyketide for the propyl (C 3 
side chain) or a C 12 polyketide for the pentyl (C 5 side chain) cannabinoid series into 
either cannabigerovarin (CBGV) or cannabigerol (CBG), respectively. Research by 
Etienne de Meijer at HortaPharm B.V. in the Netherlands shows that there is a single 
allele (Pr) controlling the propyl pathway to CBGV and another allele (Pe) controlling 
the pentyl pathway to CBG. The biosyntheses of THC, cannabidiol (CBD), and 
cannabichromene (CBC) (or tetrahydrocannabivarin [THCV] , cannabidivarin [CBDV], 
or cannabichromavarin [CBCV]) are controlled by a suite of three enzymes, each con- 
trolled by a single allele: T, D, and C, respectively. The three enzymes can likely use 
either propyl CBGV or pentyl CBG for the propyl and pentyl pathways, depending on 
which substrate is available. This hypothesis was verified by Flachowsky et al. (18). 
Continued research by de Meijer et al. (19) (see Fig. 3) has shown that CBD and THC 
biosynthesis are controlled by a pair of co-dominant alleles, which code for isoforms 
of the same synthase, each with a different specificity for converting the common 
precursor CBG into either CBD or THC. The group also identified by random ampli- 
fied polymorphic DNA analysis three chemotype-associated DNA markers that show 
tight linkage to chemotype and co-dominance. 

7. Medical Values of Terpenes 

The terpenoid compounds found in Cannabis resin are numerous, vary widely 
among varieties, and produce aromas that are often characteristic of the plant's geo- 
graphic origin. Although more than 100 different named terpenes have been identified 
from Cannabis, no more than 40 known terpenes have been identified in a single plant 
sample, and many more remain unnamed (11). Terpenes are produced via multibranched 
biosynthetic pathways controlled by genetically determined enzyme systems. This situ- 
ation presents plant breeders with a wide range of possible combinations for develop- 
ing medical Cannabis varieties with varying terpenoid profiles and specifically targeted 
medical uses. Preliminary breeding experiments confirm that the terpenoid profiles of 
widely differing parents are frequently reflected in the hybrid progeny. 

Only recently have Cannabis essential oils become economically important as 
flavorings and fragrances (17). Early Cannabis medicines were formulated from alco- 
holic whole flower or resin extracts and contained terpenes, although they were not 
recognized to be of medical importance. Several of the monoterpenes and sesquiterpe- 
nes found in Cannabis and derived from other botanical and synthetic sources are 
used in commercial medicines. Other as-yet-unidentified terpenes may be unique to 
Cannabis. The highly variable array of terpenoid side-chain substitutions results in a 
range of human physiological responses. Certain terpenes stimulate the membranes of 
the pulmonary system, soothe the pulmonary passages, and facilitate the absorption of 
other compounds ( 15). Terpenoid compounds are incorporated into pulmonary medi- 
cal products such as bronchial inhalers and cough suppressants. Casual studies indi- 
cate that when pure THC is smoked, it produces subjectively different effects than it 
does when combined with trace amounts of mixed Cannabis terpenes. Clinical trials 



8 Watson and Clarke 



Cannabinoid Biosynthesis 

THCV CBDV CBCV THC CBD CBC 




Terpenoids 



Fig. 3. Cannabinoid biosynthesis is mediated by enzymes controlled by individual 
genes (16-18). Terpenoid biosynthesis also begins along the same general pathway 
by utilizing geraniol molecules directly. THCV, A 9 -tetrahydrocannabivarin; CBVD, 
cannabidivarin; CBCV, cannabichromavarin; THC, A 9 -tetrahydrocannabinol; CBD, 
cannabidiol; CBC, cannabichromene; CBGV, cannabigerovarin; CBG, cannabigerol. 
(Adapted from ref. 19.) 

using whole plant extracts of known cannabinoid content and varying terpenoid pro- 
files will determine whether terpenoid compounds have an effect on the pharmacoki- 
netics of the cannabinoids. 

8. Cannabis 's Origin, Domestication, and Dispersal 

Cannabis originated either in the riverine valleys of Central Asia or in northern 
South Asia along the foothills of the Himalayas and was first cultivated in China on a 
large scale for fiber and seed production and soon after in India for resin production. 
Various cultures have traditionally used Cannabis for different purposes. European 
and East Asian societies most often used Cannabis for its strong fibers and nutritious 
seeds. Species of Cannabis from these regions are usually relatively low in THC 
(average <1% dry weight), with a CBD content averaging about twice as high.* Afri- 
can, Middle Eastern, South Asian, and Southeast Asian cultures used Cannabis widely 
for its psychoactive properties and to a lesser extent for fiber and food. The vast majority 
of races from these regions are high in psychoactive THC (often 5-10%) with widely 
varying CBD content (0-5%). Early on, traders spread the South Asian section of the 
Cannabis gene pool far and wide from eastern Africa to Sumatra and eventually to the 



*THC is the primary psychoactive compound produced by Cannabis, and nonpsychoactive CBD is the 
other most common naturally occurring cannabinoid. 



Cannabis and Natural Cannabis Medicines 



9 



semi-tropical New World. Central Asian hashish varieties, popularly called "indicas," 
were introduced to the West much more recently. Drug Cannabis use was adopted by 
indigenous cultures in many of these locations, and highly psychoactive races evolved. 
All modern drug varieties used as medical Cannabis are derived from these two tradi- 
tional drug variety gene pools. 

Certainly, the enchanting psychological and effective medical effects realized 
from smoking or eating Cannabis resins, along with its value as a food and fiber plant, 
have increased predation by humans, encouraged its early domestication as a crop 
plant, and hastened its dispersal worldwide first into natural and, more recently, into 
artificial environments. 

9. The Cannabis Species Debate 

Twentieth-century taxonomists have variously characterized Cannabis. Although 
all taxonomists recognize the species Cannabis sativa, Small and Cronquist (20) sub- 
divided C. sativa into two subspecies, each with two varieties based largely on can- 
nabinoid content and traditional usage. Schultes et al. (21) divided Cannabis into three 
separate species: C. sativa, C. indica, and C. ruderalis. Several other researchers do 
not preserve C. ruderalis, but recognize both C. sativa and C. indica (22,23). We 
consider C. sativa to include all wild, hemp, and drug Cannabis races, with the pos- 
sible exception of those traditionally used for hashish production in Central Asia. These 
morphologically and chemically distinct Central Asian races deserve the separate spe- 
cific name of C. afghanica following the variety name for C. indica determined by 
Vavilov and Bukinich (23). Some Chinese races may also deserve taxonomic distinc- 
tion separate from either C. sativa or C. indica (24). Validation of these theories awaits 
further chemotaxonomic and genetic research. 

In all of these taxonomic interpretations, C. sativa represents the largest and 
most diverse taxon and is commonly referred to by marijuana breeders and growers, 
as well as medical Cannabis users, as "sativa." C. afghanica is commonly known as 
"indica" (see Fig. 4). Individual plants of these hashish varieties have their own dis- 
tinctive acrid organic aromas and are often rich in CBD as well as THC. The wide 
variety of morphological, physiological, and chemical traits encountered in Cannabis 
has proven very attractive to plant breeders for years. 

10. Drug Cannabis Breeding 

During the early 1960s, marijuana cultivation came to North America. At first, 
Cannabis seeds found in illicit shipments of marijuana were simply casually sown by 
curious smokers. Early marijuana cultivators tried any available seed in their efforts 
to grow potent plants outdoors that would consistently mature before killing frosts. 
Because most imported marijuana contained seeds, many possibilities were available. 
Early-maturing northern Mexican varieties proved to be the most favored, as they 
consistently matured at northern latitudes. The legendary domestic Cannabis varieties 
of the early and mid-1970s (such as Polly and Haze) resulted from crosses between 
early-maturing Mexican or Jamaican races and more potent, but later-maturing, Pana- 
manian, Colombian, and Thai races. 



10 



Watson and Clarke 



Traditional Cannabis Gene Pools 


C. sativa or 
"sativa" 


C. afghanica? or 
"indica" 

— 


Y- 

Fiber/Seed 


Marijuana 




Hashish 


Hashish 


Russia, 
Mediterranean 
and Far East 


South Asia, 
Southeast Asia, 
Africa 

and New World 


North India, 
Nepal, 
Middle East 
and North Africa 


Afghanistan 
and Pakistan 


Low THC / 
Med. - High CBD 


High THC/ 
Low CBD 


High THC / 
Low - Med. CBD 


High THC / 
Low - High CBD 


Most modern medical Cannabis varieties are a blend of traditional 
"sativa" marijuana varieties with "indica" hashish varieties. 



Fig. 4. The four major Cannabis gene pools originate either from C. sativa, which 
comprises the vast majority of naturally occurring hemp and drug landraces (adapted 
from ref. 25) or from C. afghanica from Central Asia, which has become a component 
in many modern drug Cannabis cultivars (1 1). THC, A 9 -tetrahydrocannabinol; CBD, 
cannabidiol. 

Initially, the new Cannabis varieties were aimed at outdoor growing. Soon oth- 
ers were specially developed for greenhouse or artificial light growing, where the 
plants are sheltered from autumn cold and the growing season can be extended by 
manipulating day length, allowing later-maturing varieties to finish. Once varieties 
that would mature under differing conditions were available, pioneering marijuana 
breeders continued selections for potency (high THC content with low CBD content) 
followed by the aesthetic considerations of flavor, aroma, and color. Continued 
inbreeding of the original favorable crosses resulted in some of the "super-sativas" of 
the 1970s, such as Original Haze, Purple Haze, Pollyanna, Eden Gold, Three Way, 
Maui Wowie, Kona Gold, and Big Sur Holy Weed. 

11. The Introduction of Indica 

Indica plants are characterized as short and bushy with broad, dark green leaves, 
which make them somewhat harder to see from afar. They nearly always mature 
quite early outdoors, from late August to early October, often stand only 1-2 m (3- 
6 ft.) tall at maturity, and produce copious resin-covered flowers and leaflets. At 
least several dozen introductions of indica were made during the middle to late 1970s. 
Afghani No. 1 and Hindu Kush were among the early indica introductions that gained 
notoriety and are still available today. Following the Soviet invasion of Afghanistan 
in 1979, many additional introductions were made from Afghanistan and northwest- 
ern Pakistan. 



Cannabis and Natural Cannabis Medicines 



7 7 



Marijuana breeders intentionally crossed varieties of early-maturing indica with 
their later-maturing sativa varieties to produce early-maturing hybrid crosses (matings 
of parents from different gene pools), and soon the majority of cultivators began to 
grow the newly popular indica x sativa hybrids. Many of the indica x sativa hybrids 
were vigorous growers, matured earlier, yielded well, and were very potent. Skunk 
No. 1 is a good example of a hybrid expressing predominantly sativa traits, and North- 
ern Lights is a good example of a hybrid expressing predominantly indica traits. By 
the early 1980s, the vast majority of all domestic sinsemilla in North America had 
likely received some portion of its germplasm from the indica gene pool, and it had 
become difficult to find the preindica, pure sativa varieties that had been so popular 
only a few years earlier. 

However, the negative characteristics of reduced potency (lower THC content); 
slow, flat, sedative, dreary effect (high CBD content); skunky, acrid aroma; and harsh 
taste quickly became associated with many indica x sativa hybrids. To consumers, 
who often prefer sativas, indica has not proven itself to be as popular as it is with 
growers. Also, the dense, tightly packed floral clusters of indica tend to hold moisture 
and to develop gray mold (Botrytis), for which the plants have little natural resistance. 
Mold causes significant losses, especially in outdoor and glasshouse crops, and was 
rarely a problem when only pure C. sativa varieties were grown. In addition, fungal 
contamination of medical Cannabis could prove a serious threat to pulmonary or 
immunocompromised patients. Although consumers and commercial cultivators of 
the late 1970s initially accepted indica enthusiastically, serious breeders of the late 
1980s began to view indica with more skepticism. Although indica may currently 
appear to be a growing bane for Cannabis connoisseurs, it has certainly been a big 
boon for the average consumer, bringing more potent and medically effective Can- 
nabis to a wider audience. Indica x sativa hybrids have proven to be well adapted to 
indoor cultivation where mold is rarely a problem. Indica x sativa varieties mature 
quickly (60-80 days of flowering), allowing four to five harvests per year, and can 
yield up to 100 g of dry flowers on plants only 1 m (3 ft.) tall. C. sativa varieties are 
too gangly and tall and take too long to mature to make them desirable for the indoor 
grower. On the other hand, sativas have unique cannabinoid and terpenoid profiles 
producing effects considered superior by many medical Cannabis users. 

Political pressure on marijuana cultivators across North America forced many 
drug Cannabis breeders to relocate to the Netherlands, where the political climate was 
less threatening. During the 1980s, several marijuana seed companies appeared in the 
Netherlands, where cultivation of Cannabis for seed production and the sale of seeds 
were tolerated. To North American and European cultivators, this meant increased 
availability of exotic high-quality drug Cannabis seeds and presented yet more possi- 
bilities to find varieties that were the most medically effective for individual indica- 
tions and patients. Cannabis seed sales continue in the Netherlands today. 

12. Advances in Medical Cannabis Research 

Cannabis available to the medical user comes in two commonly available types. 
Marijuana (domestically produced or imported Cannabis flowers) is nearly always 
grown from high-THC varieties (up to 30% dry weight in trimmed female flowers) 



72 



Watson and Clarke 



and contains very little CBD. Very high THC with negligible CBD profiles of modern 
sinsemilla varieties result from marijuana growers sampling single plants and making 
seed selections from vigorous individuals with high levels of psychoactivity. Unique 
individuals may also be vegetatively propagated, thereby fixing the high-THC geno- 
type in the clonal offspring. 

Commercially available imported hashish or charas (compressed Cannabis resin) 
is collected from varieties that are predominantly THC (up to 10%) but that often 
contain up to 5% CBD as well. Imported hashish is produced by bulk processing large 
numbers of plants. Growers rarely make seed selections from individual, particularly 
potent plants, and therefore without human intervention the CBD content tends to be 
closer to that of THC. Hashish cultivars are usually selected for resin quantity rather 
than potency, so the farmer chooses plants and saves seeds by observing which ones 
produce the most resin, unaware of whether it contains predominantly THC or CBD. 
Populations grown from imported indica seeds contain approx 25% plants that are 
rich in CBD with little THC, 50% that contain moderate amounts of both CBD and 
THC, and 25% that contain little CBD and are rich in THC* Marijuana breeders 
utilized only the high-THC indica individuals in crosses, thereby promoting high THC 
synthesis and suppressing CBD. 

CBD is suspected of having modifying physiological and psychological effects 
on the primary psychoactive compound THC, and in a medical setting it may also 
have useful modulating effects on THC or valuable effects of its own. However, ana- 
lytical surveys of 80 recreational and medical Cannabis varieties in the Netherlands 
(26) and 47 samples in California (27) show that nearly every sample contained pre- 
dominantly THC with little if any CBD or other cannabinoids. Higher levels of THC 
(and other medically effective cannabinoid and terpenoid compounds) in medical 
Cannabis are healthier for patients using smoked Cannabis because they can smoke 
less to achieve the same dosage and effect. Recently developed mechanical resin- 
collecting techniques combined with high-potency Western cultivars are used to make 
very potent and pure hashish of more than 50% THC and almost no CBD (see Fig. 5). 

Proponents of medical Cannabis, especially traditional hashish users, claim that 
the additional benefits of herbal preparations are a result, at least in part, of the pres- 
ence of other cannabinoids such as CBD. Because THC (with traces of CBD) is the 
prominent cannabinoid found in most domestically produced North American and 
European marijuana and hashish, how will medical users gain legitimate legal access 
to other potentially effective cannabinoids? 

13. The Future of Medical Cannabis 

Cannabis breeders are continually searching for new sources of exotic germplasm 
and will develop new varieties that will prove particularly effective as medicines. 

*The ratio of THC to CBD usually approached 1 : 1 in populations unselected for cannabinoid content, 
and the amounts of cannabinoids are rather low. Industrial hemp varieties have been selected for unnatu- 
rally low levels of THC (European Union regulations stipulate <0.3% dry weight) and much higher levels 
of CBD, whereas sinsemilla varieties have been selected for unnaturally high levels of THC (>20% dry 
weight) at the expense of CBD. 



Cannabis and Natural Cannabis Medicines 



13 



Sources of recreational and medical Cannabis 




+ 



9 



9 



Male and female plants 



Female plants only 



Seeded Cannabis 



Vegetative cuttings 



Seeds Traditional 



Seedless Cannabis flowers 



Hashish Resi 

Sowing Grain 

Seed Seed THC + CBD 



Marijuana Modern 
"sin semilla" Hashish 
Very High THC / Very Low CBD 



Fig. 5. Both recreational and medical Cannabis typically originate from either seeded 
plants used primarily for traditional hashish production or seedless plants grown 
primarily for "sinsemilla" marijuana and occasionally for modern hashish production. 
THC, A 9 -tetrahydrocannabinol; CBD, cannabidiol. 

Pure indica varieties are still highly prized breeding stock, and new indica introduc- 
tions from Central Asia are occasionally received. Sativa varieties from Mexico, South 
Africa, and Korea are gaining favor with breeders because they mature early but do 
not suffer from the drawbacks of many indicas. Recently, Cannabis breeders have 
become more interested in variations in subjective effects between different clones 
and are developing varieties with enhanced medical efficacy based on feedback from 
medical Cannabis users. 

Genetic modification has also reached Cannabis. Researchers in Scotland have 
successfully transferred genes for gray mold resistance to an industrial hemp variety 
(28). Because Botrytis is one of the leading pests of Cannabis, causing crop loss and 
contaminating medical supplies, the transfer of resistance into medical varieties would 
be of great value. In addition, other agronomically valuable traits may also be trans- 
ferred to Cannabis, such as additional pest resistance, increased yields of medically 
valuable compounds, tolerance of environmental extremes, and sexual sterility. How- 
ever, so far the acceptance of genetically modified (GM) organisms has been timid. 
The European Union, for example, has installed strict regulations to prevent the acci- 
dental release of GM crop plants, and production of GM Cannabis in the European 
Union may be impractical. Cannabis presents a particularly high risk for transmitting 
genetically modified genes to industrial hemp crops and weedy Cannabis because it is 
wind-pollinated. If sterile female GM clones could be developed and used for produc- 
tion, then gene transfer would be blocked. Genes coding for cannabinoid biosynthesis 
might also be transferred from Cannabis to less politically sensitive organisms. 

GW Pharmaceuticals Ltd. in the United Kingdom is engaged in the development 
of prescription medicines derived from Cannabis and, as part of its research program 



14 



Watson and Clarke 



to develop novel cannabinoid medicines, supports an ongoing breeding project to 
develop high-yielding Cannabis cultivars of known cannabinoid profile. The aims of 
this research are to create varieties that produce only one of the four major cannab- 
inoid compounds (e.g., THC, CBD, CBC, CBG, or their propyl homologs) as well as 
selected varieties with consistently uniform mixed cannabinoid and terpenoid pro- 
files. These uniform profiles allow for the formulation of nonsmoked medicinal prod- 
ucts, which can meet the strict quality standards of international regulatory authorities. 
A sublingual spray application of plant-derived THC and CBD began clinical trials 
for relief of multiple sclerosis-associated symptomology in 1999. These clinical trials 
have gone on to include patients with neuropathic pain and cancer pain. 

14. Conclusion 

Cannabis has had a long association with humans, and anecdotal evidence for its 
medical efficacy is plentiful. Since the 1970s, modern North American and European 
drug Cannabis varieties have resulted largely from crosses made by clandestine breeders 
between South Asian sativa marijuana varieties that spread early throughout South 
and Southeast Asia, Africa, and the New World and Central Asian indica hashish 
varieties. These hybrid varieties are now commonly used in Western societies for 
medical Cannabis. 

Largely as a response to increased law enforcement and the limited commercial 
availability of high-quality medical grade Cannabis, patients growing their own plants 
and self-medicating is a trend rapidly spreading across North America, Europe, and 
around the globe. The political climate surrounding medical Cannabis legislation has 
become more informed, compassionate, and lenient. Cannabis cultivation for personal 
medical use will eventually be legalized or tolerated in many jurisdictions, if not by the 
public openly favoring legalization, then by increasing governmental awareness of the 
inefficiency inherent in attempted prohibition of a popular and effective medicine. 

Pharmaceutical research companies are developing new natural cannabinoid for- 
mulations and delivery systems that will meet government regulatory requirements. 
As clinical trials prove successful and the understanding of Cannabis' 's efficacy and 
safety as a modern medicine spreads, patients can look forward to a steady flow of 
new Cannabis medicines providing effective relief from a growing number of indica- 
tions. 

References 

1. Clarke, R. C. (1981) Marijuana Botany, Berkeley: Ronin Publishing. 

2. Mandolino, G. and Ranalli, P. (1999) Advances in biotechnological approaches for hemp 
breeding and industry, in Advances in Hemp Research. (Ranalli, P. ,ed.), Haworth Press, 
New York, pp. 185-211. 

3. Hong, S., Song, S-J., and Clarke, R. C. (2003) Female-associated DNA polymorphisms of 
hemp (Cannabis sativa L.) /. Indust. Hemp 1, 5-9. 

4. Small, E. and Antle, T. (2003) A preliminary study of pollen dispersal in Cannabis sativa 
in relation to wind direction. /. Indust. Hemp 8, 37-50. 

5. Deferne, J-L. and Pate, D. W. (1996) Hemp seed oil: a source of valuable essential fatty 
acids. J. Int. Hemp Assoc. 3, 1, 4-7. 



Cannabis and Natural Cannabis Medicines 



15 



6. Grigoriev, O. V. (2002) Application of hempseed (Cannabis sativa L.) oil in treatment of 
ear, nose and throat (ENT) disorders. J. Indus t. Hemp 7, 5-15. 

7. Meier, C. and Mediavilla, V. (1998) Factors influencing the yield and the quality of hemp 
{Cannabis sativa L.) essential oil. J. Int. Hemp Assoc. 5, 16-20. 

8. Liu, Y. and Tang, X. (1984) Green seedling of hemp acquired by tissue culture. China's 
Fibre Crops 2, 19, 29 [in Chinese]. 

9. Hendriks, H., Malingre, T. M., Batterman, S., and Bos, R. (1978) The essential oil of Can- 
nabis sativa L. Pharm. Weekbl. 113, 413-424. 

10. Ross, R. A. and ElSohly, M. A. (1996) The volatile oil composition of fresh and air-dried 
buds of Cannabis sativa L. J. Nat. Prod. 59, 49-5 1 . 

11. Clarke, R. C. (1998) Hashish.', Red Eye Press, Los Angeles. 

12. Pate, D. W. (1994) Chemical ecology of Cannabis. J. Int. Hemp Assoc. 1, 29, 32-37. 

13. McPartland, J., Clarke, R. C, and Watson, D. P. (2000) Hemp Diseases and Pests, CAB 
International, Wallingford, UK. 

14. Briosi, G. and Tognini, F. (1894) Intorno alia anatomia della canapa (Cannabis sativa L.) 
parte prima — organi sessual, Atti dell' Instituto Botanico di Pavia, Serie I, Vol. 3. 

15. McPartland, J. and Mediavilla, V. (2002) Cannabis and Cannabinoids: Pharmacology and 
Therapeutic Potential (Grotenhermen, F. and Russo, E., eds.), Haworth Integrative Heal- 
ing Press, New York, pp. 401-409. 

16. Taura, F., Morimoto, S., Shoyama, Y., and Mechoulam, R. (1995) First direct evidence for the 
mechanism of delta- 1 -tetrahydrocannabinol acid biosynthesis. J. Am. Chem. Soc. 117, 9766-9767. 

17. Taura, F., Morimoto, S., and Shoyama, Y. (1996) Purification and characterization of 
cannabidiolic-acid synthase from Cannabis sativa L. Biochemical analysis of a novel en- 
zyme that catalyzes the oxidocyclization of cannabigerolic acid to cannabidiolic acid. /. 
Biol. Chem. 271, 17411-17416. 

18. Flachowsky, H., Schumann, E., Weber, W. E., and Peil, A. (2000) AFLP-marker for male 
plants of hemp (Cannabis sativa L.) Poster presented at the 3 rd Bioresource Hemp Sympo- 
sium, Wolfsburg, Germany, September 13-16. 

19. de Meijer, E. P. M., Bagatta, M., Carboni, A., et al. (2003) The inheritance of chemical 
phenotype in Cannabis sativa L. Genetics 163, 335-346. 

20. Small, E. and Cronquist, A. (1976) A practical and natural taxonomy for Cannabis. Taxon 
25,405-435. 

21. Schultes, R. E., Klein, W. M., Plowman, T., and Lockwood, T. E. (1974) Cannabis: an ex- 
ample of taxonomic neglect. Botanical Museum Leaflets, Harvard University 23, 337-364. 

22. Serebriakova, T. I. (1940) Fiber plants, in Flora of Cultivated Plants. Vol.4, Parti (Wulff, 
E. V., ed.), State Printing Office, Moscow and Leningrad [in Russian]. 

23. Vavilov, N. and Bukinich, D. D. (1929) Agricultural Afghanistan. Bull. Appl. Bot. Genet. 
Plant Breed.Supp. 33, 378-382, 474, 480, 584-585, 604. 

24. Hillig, K. W. and Mahlberg, P. G. (2004) Genetic evidence for speciation in Cannabis 
(Cannabaceae). Genet. Resources Crop Evol. 52, 161-180. 

25. de Meijer, E. P. M. (1999) Cannabis germplasm resources, in Advances in Hemp Research 
(Ranalli, P., ed.), Haworth Press, New York, pp. 133-151. 

26. HortaPharm, personal communication (1998) HortaPharm BV develops industrial Can- 
nabis cultivars and provided the starting materials GW Pharmaceuticals breeding project 
in the United Kingdom. 

27. Gierenger, D. (1999) Medical Cannabis potency testing. Bull. Multidisc. Assoc. Psychedel. 
Stud. 9, 20-22. 

28. MacKinnon, L. (2003) Genetic transformation of Cannabis sativa Linn: a multi purpose 
fibre crop, doctoral thesis, University of Dundee, Scotland. 



Chapter 2 



Chemistry and Analysis 

of Phytocannabinoids 

and Other Cannabis Constituents 

Rudolf Brenneis en 

1. The Chemistry of Phytocannabinoids and Noncannabinoid-Type 

Constituents 

1.1. Phytocannabinoids 

1.1.1. Introduction 

The Cannabis plant and its products consist of an enormous variety of chemi- 
cals. Some of the 483 compounds identified are unique to Cannabis, for example, the 
more than 60 cannabinoids, whereas the terpenes, with about 140 members forming 
the most abundant class, are widespread in the plant kingdom. The term "cannab- 
inoids" represents a group of C 2] terpenophenolic compounds found until now uniquely 
in Cannabis sativa L. (1). As a consequence of the development of synthetic cannab- 
inoids (e.g., nabilone [2], HU-211 [dexanabinol; ref. {3j, or ajulemic acid [CT-3; ref. 
4]) and the discovery of the chemically different endogenous cannabinoid receptor 
ligands ("endocannabinoids," e.g., anandamide, 2-arachidonoylglycerol) (5,6), the term 
"phytocannabinoids" was proposed for these particular Cannabis constituents (7). 

1.1.2. Chemistry and Classification 

So far, 66 cannabinoids have been identified. They are divided into 10 subclasses 
(8-10) (see Table 1). 

From: Forensic Science and Medicine: Marijuana and the Cannabinoids 
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey 

17 



Brenneisen 



Table 1 
Cannabinoids 



Compound 


Structure 


Main pharmacological 
characteristics 


Cannabigerol class 




| OH 










Cannabigerolic acid 


I LI 

|l R 3 ° R 2 


Antibiotic 


(CBGA) 


Ri =COOH, R 2 = C 5 Hn, R 3 = H 




Cannabigerolic acid 


Ri = COOH, R2 = C5H11, R3 = 




monomethylether 


CH 3 




(CBGAM) 










Antibiotic 


Cannabigerol 




Antifungal 


(CBG) 


R-i = H, R2 = C5H11, R3 = H 


Anti-inflammatory 
Analgesic 


Cannabigerol 






monomethylether 
(CBGM) 


Ri = H, R2 = C5H11, R3 = CH3 




Cannabigerovarinic 






acid 
(CBGVA) 


Ri = COOH, R 2 = C 3 H 7 , R 3 = H 




Cannabigerovarin 
(CBGV) 


Ri — H, R2 — C 3 H7, R 3 — H 





( continued) 



1. Cannabigerol (CBG) type: CBG was the first cannabinoid identified (11), and its pre- 
cursor cannabigerolic acid (CBGA) was shown to be the first biogenic cannabinoid 
formed in the plant (12). Propyl side-chain analogs and a monomethyl ether deriva- 
tive are other cannabinoids of this group. 

2. Cannabichromene (CBC) type: Five CBC-type cannabinoids, mainly present as C5- 
analogs, have been identified. 

3. Cannabidiol (CBD) type: CBD was isolated in 1940 ( 13), but its correct structure was 
first elucidated in 1963 by Mechoulam and Shvo (14). Seven CBD-type cannabinoids 
with CI to C5 side chains have been described. CBD and its corresponding acid CBDA 



Chemistry of Cannabis Constituents 

Table 1 (continued) 



19 



Compound 



Structure 



Main pharmacological 
characteristics 



Cannabichromene class 



Cannabichromenic acid 
(CBCA) 




Ri — COOH, R2 — C5H11 



Cannabichromene 
(CBC) 



R1 — H, R2 — C5H1 



Anti-inflammatory 
Antibiotic 
Antifungal 
Analgesic 



Cannabichromevarinic acid 
(CBCVA) 



R1 = COOH, R 2 = C3H7 



Cannabichromevarin 
(CBCV) 



R1 — H, R2 - C3H7 



Cannabidiol class 



Cannabidiolic acid 
(CBDA) 




Ri = COOH, R2 = C 5 Hii,R 3 = H 



Antibiotic 



Cannabidiol 
(CBD) 



R1 — H, R 2 — C5H11, R3 — H 



Anxiolytic 
Antipsychotic 
Analgesic 
Anti-inflammatory 
Antioxydant 
Antispasmodic 



( continued) 

are the most abundant cannabinoids in fiber-type Cannabis (industrial hemp). Iso- 
lated in 1955, CBDA was the first discovered cannabinoid acid. 
4. A 9 -Tetrahydrocannabinol (THC) type: Nine THC-type cannabinoids with CI to C5 
side chains are known. The major biogenic precursor is the THC acid A, whereas 



20 Brenneisen 



Table 1 (continued) 



Compound 


Structure 


Main 
pharmacological 
characteristics 








Cannabidiol 
monomethylether 
(CBDM) 


R1 = H, R2 - C5H11, R3 — CH3 




Cannabidiol-C 4 
(CBD-C4) 


R1 = H, R2 = C4H9, R3 = H 




Cannabidivarinic acid 
(CBDVA) 


R1 = COOH, R 2 = C3H7, R 3 = H 




Cannabidivarin 
(CBDV) 


R1 = H, R2 = C3H7, R3 = H 




Cannabidiorcol 
(CBD-d) 


R1 — H, R2 = CH3, R3 — H 




Delta-9-tetrahydrocannabinol class 


Delta-9- 
tetrahydrocannabinolic acid A 
(THCA-A) 


(a] oh 

10a * r n 

R1 = COOH, R2 = C 5 Hn, R3 = H 




Delta-9- 
tetrahydrocannabinolic acid B 
(THCA-B) 


R1 = H, R 2 = C a H 11 , R 3 = COOH 





( continued) 



THC acid B is present to a much lesser extent. THC is the main psychotropic prin- 
ciple; the acids are not psychoactive. THC (6a,10a-fra«5-6a,7,8,10a-tetrahydro-6,6,9- 
trimethyl-3-pentyl-6H-dibenzo[fo,<i]pyran-l-ol) was first isolated in 1942 ( 15), but the 
correct structure assignment by Gaoni and Mechoulam took place in 1964 (16). 



Chemistry of Cannabis Constituents 

Table 1 (continued) 



21 



Compound 


Structure 


Main 
nharmaeoloaieal 

Ml IQI 1 1 IQVfV ■ V M 1 Wtl 1 

characteristics 


Delta-9-tetrahydrocannabinol 
(THC) 


R-i = H, R2 = C5H11, R3 = H 


Euphoriant 
Analgesic 
Anti-inflammatory 
Antioxidant 
Antiemetic 


Delta-9- 
tetrahydrocannabinolic 
acid-C 4 
(THCA-C 4 ) 


R1 = COOH, R 2 = C4H9, R 3 = H 
or 

R1 = H, R 2 = C 4 H 9 , R 3 = COOH 




Delta-9- 
tetrahydrocannabinol-C 4 
(THC-C 4 ) 


r*C H — ri |"C — 1 > A H A l"v — H 
1 \^ 1 1, 1 \^ V-/41 iy, 1 \j 1 1 




Delta-9- 
tetrahydrocannabivarinic acid 
(THCVA) 


R1 = COOH R9 = CqH 7 Rt = H 




Delta-9- 
tptrahvdrnrannflhivarin 

icli a i 1 yui \j\sdi 11 ict 1 v a 1 11 1 

(THCV) 


R1 = H, R2 = C3H7, R3 = H 


Analgesic 
Fi inhoriant 

LUUI IUI ICII 11 


Delta-9- 
tetrahydrocannabiorcolic acid 
(THCA-d) 


R1 = COOH, R 2 = CH 3 , R 3 = H 
or 

R1 = H, R 2 = CH 3 , R 3 = COOH 




Delta-9- 
tetrahydrocannabiorcol 
(THC-d) 


R1 — H, R2 = CH3, R3 — H 





( continued) 

5. A 8 -THC type: A 8 -THC and its acid precursor are considered as THC and THC acid 
artifacts, respectively. The 8,9 double-bond position is thermodynamically more stable 
than the 9,10 position. A 8 -THC is approx 20% less active than THC. 



22 



Table 1 (continued) 



Brenneisen 



Compound 


Structure 


Main 






pharmacological 






characteristics 




] OH 




Delta-7-c/s-iso- 






tetrahydrocannabivarin 














Ri — C3H7 




Delta-8-tetrahydrocannabinol class 










Delta-8- 












tetrahydrocannabinolic acid 


= I il 




(A 8 -THCA) 








Ri = COOH, R 2 = C 5 Hn 




Delta-8- 




Ri — H, R2 — C5H11 


Similar to THC 


tetrahydrocannabinol 




(less potent) 


(A 8 -THC) 






Cannabicyclol class 




\y oh 










Cannabicyclolic acid 






(CBLA) 


^^^0'^^^R 2 






Ri = COOH, R 2 = C 5 Hn 




Cannabicyclol 


Ri = H, R2 = C5H11 




(CBL) 






Cannabicyclovarin 


Ri = H, R2 = C3H7 




(CBLV) 







( continued) 



6. Cannabicyclol (CBL) type: Three cannabinoids characterized by a five-atom ring and 
Cj-bridge instead of the typical ring A are known: CBL, its acid precursor, and the C 3 
side-chain analog. CBL is known to be a heat-generated artifact from CBC. 

7. Cannabielsoin (CBE) type: Among the five CBE-type cannabinoids, which are arti- 
facts formed from CBD, are CBE and its acid precursors A and B. 



Chemistry of Cannabis Constituents 

Table 1 (continued) 



23 



Compound 


Structure 


Main 
pharmacological 
characteristics 


Cannabielsoin class 


Cannabielsoic acid A 
(CBEA-A) 


hctV^r 

R 

Ri =COOH, R2 = C 5 Hn, R 3 = H 




Cannabielsoic acid B 
(CBEA-B) 


Ri = H, R2 = C5H11, R3 = COOH 




Cannabielsoin 
(CBE) 


R1 = H, R2 = C5H11, R3 = H 




Cannabinol and cannabinodiol class 


Cannabinolic acid 
(CBNA) 




h! ? Ri 

Ri = H, R 2 = COOH, R 3 = C5H11 




Cannabinol 
(CBN) 


R-i — H, R2 — H, R3 — C5H11 


Sedative 
Antibiotic 
Anticonvulsant 
Anti-inflammatory 



(continued) 

8. Cannabinol (CBN) and Cannabinodiol (CBND) types: Six CBN- and two CBND-type 
cannabinoids are known. With ring A aromatized, they are oxidation artifacts of THC 
and CBD, respectively. Their concentration in Cannabis products depends on age and 
storage conditions. CBN was first named in 1 896 by Wood et al. (1 7) and its structure 
elucidated in 1940 (18). 



24 Brenneisen 



Table 1 (continued) 



Compound 


Structure 


Main 
pharmacological 
characteristics 


Cannabinol methylether 
(CBNM) 


R1 = CH3, R2 = H, R3 = C5H11 




Cannabinol-C 4 
(CBN-C 4 ) 


R1 = H, R2 = H, R3 = C4H9 




Cannabivarin 
(CBV) 


R1 — H, R2 — H, R3 — C3H7 




Cannabinol-C2 
(CBN-C2) 


R1 = H, R2 = H, R3 = C2H5 




Cannabiorcol 
(CBN-C1) 


R1 = H, R2 = H, R3 = CH3 




Cannabinodiol 
(CBND) 


R = C5H11 




Cannabinodivarin 
(CBVD) 


R = C3H7 





( continued) 



9. Cannabitriol (CBT) type: Nine CBT-type cannabinoids have been identified, which 
are characterized by additional OH substitution. CBT itself exists in the form of both 
isomers and the racemate, whereas two isomers (9-a- and 9-b-hydroxy) of CBTV 
were identified. CBDA tetrahydrocannabitriol ester (ester at 9-hydroxy group) is the 
only reported ester of any naturally occurring cannabinoids. 
10. Miscellaneous types: Eleven cannabinoids of various unusual structure, e.g., with a furano 
ring (dehydrocannabifuran, cannabifuran), carbonyl function (cannabichromanon, 10- 
oxo-8-6a-tetrahydrocannabinol), or tetrahydroxy substitution (cannabiripsol), are known. 



Chemistry of Cannabis Constituents 25 



Table 1 (continued) 



Compound 


Structure 


Main 
pharmacological 
characteristics 


Cannabitriol class 




\ OH 
Rl V^Y- R2 OH 




odnriduiinui 






(CBT) 


/ \O^^R 3 
Ri — H, R2 — OH, R3 — C5H11 




1 O-Ethoxy-9-hydroxy-delta- 
6a-tetrahydrocannabinol 


R1 H, R2 OC2H51 R3 C5H11 




8,9-Dihydroxy-delta-6a- 
tetrahydrocannabinol 


R1 — OH, R2 — H, R3 — C5H-11 




Cannabitriolvarin 
(CBTV) 


R1 = H, R2 = OH, R3 = C3H7 




Ethoxy-cannabitriolvarin 
(CBTVE) 


R1 = H, R2 ~ OC2H5, R3 = C3H7 




Miscellaneous cannabinoids class 


Dehydrocannabifuran 






(DCBF) 







( continued) 



1.1.3. THC Potency Trends 

From 1980 to 1997, a total of 35,213 samples of confiscated Cannabis products 
{Cannabis, hashish, hashish oil) representing more than 7717 tons seized in the United 
States were analyzed by gas chromatography (GC) (19). The mean THC concentra- 
tion increased from less than 1.5% in 1980 to 4.2% in 1997. The maximum levels 
found were 29.9 and 33.1% in marijuana and sinsemilla Cannabis, respectively. Hashish 



26 



Table 1 (continued) 



Brenneisen 



Compound 


Structure 


Main 
pharmacological 
characteristics 










I 




Cannabifuran 






(CBF) 








OH 




Cannabichromanon 
(CBCN) 








\) 




Cannabicitran 


i/i 




(CBT) 


"XO^-^C.H^ 






r oh 




1 0-Oxo-delta-6a- 






tetrahydrocannabinol 






(OTHC) 












Delta-9-c/s- 






tetrahydrocannabinol 






(cis-THC) 







( continued) 



and hashish oil showed no particular potency trend. The highest THC concentrations 
measured were 52.9 and 47.0%, respectively. Two studies performed in Switzerland 
from 1981 to 1985 (20) and 2002 to 2003 (21) found mean THC concentrations in 
marijuana samples of 1.4 and 12.9%, respectively. Maximum levels were 4.8 and 28.4%, 
respectively. Reasons for this enormous increase in potency include progress in breed- 



Chemistry of Cannabis Constituents 

Table 1 (continued) 



27 



Compound 



Structure 



Main 
pharmacological 
characteristics 



3,4,5,6-Tetrahydro-7- 
hydroxy-alpha-alpha-2- 
trimethyl-9-n-propyl-2,6- 
methano-2H-1-benzoxocin- 
5-methanol 
(OH-iso-HHCV) 



Cannabiripsol 
(CBR) 





C 5 H 11 



Trihydroxy-delta-9- 
tetrahydrocannabinol 
(triOH-THC) 




ing, the tendency to cultivate under indoor conditions, and the worldwide access to 
and exchange of seeds originating from high-THC cultivars via the Internet (22). 

1.1.4. THC in Hemp Seed Products 

The presence of THC in hemp seed products is predominantly the result of exter- 
nal contact of the seed hull with cannabinoid-containing resins in bracts and leaves 
during maturation, harvesting, and processing (23-25). The seed kernel is not entirely 
free of THC but contains, depending on the hemp variety, less than 0.5 [ig/g. Studies 
on hemp oil conducted in the United States, Germany, and Switzerland have shown 
THC levels from 11 to 117, 4 to 214, and up to 3568 [ig/g, respectively (24,26-28). 
These high levels were attributed to seeds from THC-rich, "drug-type" varieties, and 
the lack of adequate cleaning procedures. In recent years, more careful seed drying 
and cleaning have considerably lowered the THC content of seeds and oil available in 
the United States (23,24). However, oils and hulled seeds containing 10-20 and 2-3 |J,g/g 
THC, respectively, are still found on the US market. 



28 



Brenneisen 



1.2. Noncannabinoid-Type Constituents 

1.2.1. Terpenoids 

The typical scent of Cannabis results from about 140 different terpenoids. Iso- 
prene units (C 5 H g ) form monoterpenoids (C, skeleton), sesquiterpenoids (C 15 ), 
diterpenoids (C 20 ), and triterpenoids (C 30 ; see Table 2). Terpenoids may be acyclic, 
monocyclic, or polycyclic hydrocarbons with substitution patterns including alcohols, 
ethers, aldehydes, ketones, and esters. The essential oil (volatile oil) can easily be 
obtained by steam distillation or vaporization. The yield depends on the Cannabis 
type (drug, fiber) and pollination; sex, age, and part of the plant; cultivation (indoor, 
outdoor etc.); harvest time and conditions; drying; and storage (29-31 ). For example, 
fresh buds from an Afghani variety yielded 0.29% essential oil (32). Drying and stor- 
age reduced the content from 0.29 after 1 week and 3 months to 0.20 and 0.13%, 
respectively (32). Monoterpenes showed a significantly greater loss than sesquiterpe- 
nes, but none of the major components completely disappeared in the drying process. 
About 1.3 L of essential oil per ton resulted from freshly harvested outdoor-grown 
Cannabis, corresponding to about 10 L/ha (29). The yield of nonpollinated 
("sinsemilla") Cannabis at 18 L/ha was more than twofold compared with pollinated 
Cannabis (8 L/ha) (30). Sixty-eight components were detected by GC and GC/mass 
spectrometry (MS) in fresh bud oil distilled from high-potency, indoor-grown Can- 
nabis (32). The 57 identified constituents were 92% monoterpenes, 7% sesquiterpe- 
nes, and approx 1% other compounds (ketones, esters; refs. 9 and 32). The dominating 
monoterpenes were myrcene (67%) and limonene (16%). In the essential oil from 
outdoor-grown Cannabis, the monoterpene concentration varied between 47.9 and 
92. 1% of the total terpenoid content (29). The sesquiterpenes ranged from 5.2 to 48.6%. 
The most abundant monoterpene was (3-myrcene, followed by frarcs-caryophyllene, 
a-pinene, fraTis-ocimene, and a-terpinolene. "Drug-type" Cannabis generally con- 
tained less caryophyllene oxide than "fiber-type" Cannabis. Even in "drug-type" Can- 
nabis, the THC content of the essential oil was not more than 0.08% (29). In the 
essential oil of five different European Cannabis cultivars, the dominating terpenes 
were myrcene (21.1-35.0%), a-pinene (7.2-14.6%), a-terpinolene (7.0-16.6%), trans- 
caryophyllene (12.2.-18.9%), and a-humulene (6.1-8.7%; ref. 33). The main differ- 
ences between the cultivars were found in the contents of a-terpinolene and a-pinene. 

Other terpenoids present only in traces are sabinene, a-terpinene, 1,8-cineole 
(eucalyptol), pulegone, y-terpinene, terpineol-4-ol, bornyl acetate, a-copaene, 
alloaromadendrene, viridiflorene, (3-bisabolene, y-cadinene, fra?is-(3-farnesene, trans- 
nerolidol, and P-bisabolol (29,32,34). 

1.2.2. Hydrocarbons 

The 50 known hydrocarbons detected in Cannabis consist of rc-alkanes rang- 
ing from C 9 to C 39 , 2-methyl-, 3-methyl-, and some dimethyl alkanes (10,35). The 
major alkane present in an essential oil obtained by extraction and steam distilla- 
tion was the n-C 29 alkane nonacosane (55.8 and 10.7%, respectively). Other abun- 
dant alkanes were heptacosane, 2,6-dimethyltetradecane, pentacosane, hexacosane, 
and hentriacontane. 



Chemistry of Cannabis Constituents 29 

Table 2 

Terpenoids of the Essential Oil From Cannabis 









Percentage 


Compound 


Class 3 


Structure 


Ref. 32 


Ref. 29 


Myrcene 


M 


i 

X 


32.9-67.1 


29.4-65.8 


Limonene 


M 




16.3-17.7 


0.9-1.5 












Linalool 


M 




2.8-5.1 


0.002 


frans-Ocimene 


M 


f 




2.3-5.7 



(continued) 



1.2.3. Nitrogen-Containing Compounds 

Cannabis sativa L. is one of the rare psychotropic plants in which the central 
nervous system activity is not linked to particular alkaloids. However, two spermi- 
dine-type alkaloids (see Table 3) have been identified among the more than 70 nitro- 
gen-containing constituents. Other nitrogenous compounds found are the quartenary 
bases choline, trigonelline, muscarine, isoleucine betaine, and neurine. Among the 8 
amides are, for example, /V-frans-feruloyltyramine, Af-/?-coumaroyltyramine, and iV- 
frafts-caffeoyltyramine (see Table 4). Five lignanamide derivatives have been iso- 
lated, including cannabisin A, B, C, and D (see Table 5). 

Twelve simple amines, including piperidine, hordenine, methylamine, ethylamine, 
and pyrrolidine, are known. The three proteins detected are edestin, zeatin, and 



30 



Brenneisen 



Table 2 (continued) 



Compound 



Class 3 



Structure 



Percentage 



Ref. 32 Ref. 29 



beta-Pinene 



M 




alpha-Pinene 



M 




2.2-2.5 



1.3-1.6 




1.1-1.6 



6.0-8.4 



beta-Caryophyllene 




1 .3-5.5 



19.5-31.4 



delta-3-Carene 



M 




0.8-1.0 



frans-gamma-Bisabolene 




0.7-3.9 



( continued) 



zeatinnucleoside; the six enzymes are edestinase, glucosidase, polyphenoloxydase, 
peptidase, peroxidase, and adenosine-5-phosphatase. The 18 amino acids are of a struc- 
ture common for plants. 

1.2.4. Carbohydrates 

Common sugars are the predominant constituents of this class. Thirteen 
monosacharides (fructose, galactose, arabinose, glucose, mannose, rhamnose, etc.), 
two disaccharides (sucrose, maltose), and five polysaccharides (raffinose, cellulose, 
hemicellulose, pectin, xylan) have been identified so far. In addition, 12 sugar alcohols 



Chemistry of Cannabis Constituents 31 



Table 2 (continued) 











Percentage 


Compound 


Class 3 


Structure 


Ref. 32 


Ref. 29 


/rans-alpha-Farnesene 


S 






0.6-2.7 




beta-Fenchol 


M 




■\ OH 


0.4-1.0 




beta-Phellandrene 


M 


ij 

X 






0.4 


alpha-Humulene 


S 






0.3-2.1 


3.3-3.4 


(alpha-Caryophyllene) 


















'''/ 






Guajol 


S 




OH 


0.3-1.8 




alpha-Guaiene 


S 




0.3-1.2 





( continued) 



and cyclitols (mannitol, sorbitol, glycerol, inositol, quebrachitol, etc.) and two amino 
sugars (galactosamine, glucosamine) were found. 

7.2.5. Flavonoids 

Twenty-three commonly occurring flavonoids have been identified in Cannabis, 
existing mainly as C-/0- and O-glycosides of the flavon- and flavonol-type aglycones 



32 Brenneisen 

Table 2 (continued) 













Percentage 


Compound 


Class 3 


Structure 




Ref. 32 


Ref. 29 


alpha-Eudesmol 


S 


T ^ 




^OH 


0.2-1.4 




Terpinolene 


M 


i 

4 




0.2-1.1 


3.4-5.6 


alpha-Selinene 


S 


k\ Jn. 

T 1=1 






0.2-0.7 




alpha-Terpineol 


M 


X 

OH 






0.2-0.5 




Fenchone 


M 






r 


0.2-0.4 




Camphene 


M 


a ■ 


C 




0.2-0.4 





( continued) 



apigenin, luteolin, quercetin, and kaempferol (see Table 6; ref. 36). Orientin, vitexin, 
luteolin-7-O-glucoside, and apigenin-7-Oglucoside were the major flavonoid glyco- 
sides present in low-THC Cannabis cultivars (37). The cannflavins A and B are unique 
to Cannabis (38,39). 

1.2.6. Fatty Acids 

A total of 33 different fatty acids, mainly unsaturated fatty acids, have been iden- 
tified in the oil of Cannabis seeds. Linoleic acid (53-60% of total fatty acids), a- 



Chemistry of Cannabis Constituents 33 

Table 2 (continued) 



Compound 


Class 3 


Structure 


Percentage 


Ref. 32 


Ref. 29 


c/s-Sabinene hydrate 


M 






>H 


0,2-0.5 




c/s-Ocimene 


M 






traces-0.2 


0.2-0.3 


beta-Eudesmol 


S 




H 




~~OH 


0.1-1.1 




beta-Selinene 


S 




H 






0.1-0.6 


0.2-0.4 


alpha-frans- 
Bergamotene 


S 








0.1-0.5 


0.4-0.6 


gamma-Eudesmol 


S 




in 






0.1-0.5 




Borneol 


M 






s/ 


T' OH 


0.1-0.3 


0.008 



( continued) 



linolenic acid (15-25%), and oleic acid (8.5-16%) are most common (see Table 7) 
(40). Other unsaturated fatty acids are y-linolenic acid (1^1%), stearidonic acid (0.4- 
2%), eicosanoic acid (<0.5%), c/s-vaccenic acid, and isolinolenic acid. The saturated 
fatty acids are palmitic acid (6-9%), stearic acid (2-3.5%), arachidic acid (1-3%), 
behenic acid (<0.3%), myristic acid, lignoceric acid, caproic acid, heptanoic acid, ca- 



34 Brenneisen 



Table 2 (continued) 









Percentage 


Compound 


Class 8 


Structure 


Ref. 32 


Ref. 29 


c/s-beta-Farnesene 


S 




0.1-0.3 


0.6-0.9 


gamma-Curcumene 


S 




0.1-0.3 




c/s-gamma-Bisabolene 


s 




0.1-0.3 




alpha-Thujene 


M 


i 

X 


0.1-0.2 














epi-alpha-Bisabolol 


S 




0.1-1.2 




Ipsdienol 


M 


Hoj x 


traces-0.1 





(continued) 



prylic acid, pelargonic acid, capric acid, lauric acid, margaric acid, and isoarachidic 
acid. The fatty acid spectrum of Cannabis seeds does not significantly vary in oil 
produced from drug (THC) or low-THC (hemp, fiber) type Cannabis (41). For the 
THC content of Cannabis seeds and seed oil, see Section 1.1.4. 



Chemistry of Cannabis Constituents 35 

Table 2 (continued) 





Class 3 








Percentage 


Compound 


Structure 


Ref. 32 


Ref. 29 


alpha-Ylangene 


S 




traces-0. 1 




beta-Elemene 


S 








traces-0.2 




alpha-c/s-Bergamotene 


s 








traces-0. 6 




gamma-Muurolene 


s 






traces-0. 1 








1 - 








alpha-Cadinene 


s 


I 


\^ 
H 




traces-0. 1 




alpha-Longipinene 


s 




c 




traces-0. 1 


















Caryophyllene oxide 


s 








traces-0.8 





























a M, monoterpene; S, sesquiterpene. 



1.2.7. N one annabinoid Phenols 

Thirty-four noncannabinoid phenols are known: nine with spiro-indan-type struc- 
ture (e.g., cannabispiran, isocannabispiran), nine dihydrostilbenes (e.g., cannabistilbene- 



36 Brenneisen 



Table 3 
Spermidine Alkaloids 



Compound 


Structure 










Cannabisativine 


Her 

C 5 H 11 






Anhydrocannabisativine 


V 

C 5 H 11 


Table 4 
Amides 


Compound 


Structure 






W - f ra/is- Fe ru 1 oy 1 ty ra m i n e 


HoXJ 

R - OCH 3 


W-p-Coumaroyltyramine 


R = H 


A/-fra/7S-Caffeoy Ityra m ine 


R = OH 



I, -II), three dihydrophenanthrenes (e.g., cannithrene- 1 , -2), and six phenols, phenol 
methylethers, and phenolic glycosides (phloroglucinol glucoside; see Table 8). 

1.2.8. Simple Alcohols, Aldehydes, Ketones, Acids, Esters, 
and Lactones 

Seven alcohols (e.g., methanol, ethanol, l-octene-3-ol), 12 aldehydes (e.g., 
acetaldehyde, isobutyraldehyde, pentanal), 13 ketones (e.g., acetone, heptanone-2, 2- 
methyl-2-heptene-6-one), and 21 acids (e.g., arabinic acid, azealic acid, gluconic acid) 
have been identified. 



Chemistry of Cannabis Constituents 



37 



Table 5 
Lignanamide Derivatives 

Compound Structure 



Grossamide 



Cannabisin-A 



Cannabisin-B 




R-i — R2 — R3 — H 



Cannabisin-C = R 3 = H, R 2 = CH 3 



Cannabisin-D R-, = H, R 2 = R3 = CH 3 



1.2.9. Other 

Among the 1 1 phytosterols known are campesterol, ergosterol, (3-sitosterol, and 
stigmasterol. Vitamin K is the only vitamin found in Cannabis, whereas carotene and 
xanthophylls are reported pigments. Eighteen elements were detected (e.g., Na, K, Ca, 
Mg, Fe, Cu, Mn, Zn, Hg). 



38 



Brenneisen 



Table 6 

C- and O-Glycosides Forming Flavonoid Aglycones and C-Glycosides 





Structure 








.OH 










Apigenin 




OH 




Luteolin 


HO^ 


OH 


OH 
OH 








OH 










Kaempferol 




ll I] 

>f OH 
OH 










^OH 


Quercetin 




>p oh 

OH 


OH 



(continued) 



1.3. Pharmacological Characteristics of Cannabinoids and Other 
Cannabis Constituents 

THC is the pharmacologically and toxicologically most relevant and best stud- 
ied constituent of the Cannabis plant, responsible for most of the effects of natural 
Cannabis preparations (42). (A MEDLINE search covering the period 1993-2003 and 
using the keywords "tetrahydrocannabinol" and "pharmacology" produced about 1000 
citations.) THC mainly acts through binding to the CB-1 receptor (see Chapter 6). The 
natural (-)-trans isomer of THC is 6- to 100-fold more potent than the (+)-trans iso- 
mer. A review of the pharmacology, toxicology, and therapeutic potential of Can- 
nabis, cannabinoids, and other Cannabis constituents is given in refs. 43-53. It is 
claimed that Cannabis as a polypharmaceutical herb may provide two advantages over 



Chemistry of Cannabis Constituents 

Table 6 (continued) 



39 



Compound 


Structure 




Glucose [ 




ho. X. -o. Ji Jy^ 

|^ || OH 


Orientin 


OH O 




/\ OH 

Glucose i| 






Vitexin 


OH 




OCH 3 




iY° H 






Cannflavin A 


fill 

OH O 

R 

R = H 2 C-CH=C-(CH 3 ) 2 


Cannflavin B 


R = CH 3 



single-ingredient synthetic drugs: (1) the therapeutic effects of the primary active 
Cannabis constituents may be synergized by other compounds, and (2) the side effects 
of the primary constituents may be mitigated by other compounds (34). Thus, Cannabis 
has been characterized as a "synergistic shotgun," in contrast, for example, to dronabinol 
(synthetic THC, Marinol 8 ), a single-ingredient "silver bullet" (54). A recent study 
compared the subjective effects of orally administered and smoked THC alone and 
THC within Cannabis preparations (brownies, cigarettes; refs. 55 and 56). THC and 
Cannabis in both application forms produced similar, dose-dependent subjective 
effects, and there were few reliable differences between the THC-only and whole- 
plant conditions. 

CBD is the next-best phytocannabinoid after THC. An overview of the pharma- 
cology and clinical relevance of CBD can be found in refs. 34, 57, and 58. Of clinical 
relevance could be its reported ability to reduce anxiety and the other unpleasant psy- 
chological side effects of THC. Among the underlying mechanisms is the potent inhi- 
bition of the cytochrome P450 3A1 1, which biotransforms THC to the fourfold more 
psychoactive 11-hydroxy-THC (59). 



40 



Brenneisen 



Table 7 

Unsaturated Fatty Acids From Cannabis Seed Oil 



Compound 


Structure 


Linoleic acid 








^^^COOH 


alpha-Linolenic acid 










Oleic acid 











It has been suggested that the terpenoid constituents of Cannabis modulate THC 
activity, for example, by binding to cannabinoid receptors, modulating the THC receptor 
affinity, or altering its pharmacokinetics (e.g., by changing the blood-brain barrier; 
ref. 60). Whereas the anti-inflammatory and antibiotic activity of Cannabis terpe- 
noids is known and has been used therapeutically for a long time, the serotonergic 
effect at 5-HT 1A and 5-HT 2A receptors of the essential oil, which could explain Can- 
nabis -mediated analgesia and mood alteration, has only recently been demonstrated 
(61). P-Myrcene, the most abundant monoterpene in Cannabis, has analgesic, anti- 
inflammatory, antibiotic, and antimutagenic properties (34). (3-Caryophyllene, the most 
common sesquiterpene, exhibits anti-inflammatory, cytoprotective (gastric mucosa), 
and antimalarial activity. The pharmacological effects of other Cannabis terpenes are 
discussed by McPartland and Russo (34). 

Apigenin, a flavonoid found in nearly all vascular plants, excerts a wide range of 
biological effects, including many properties shared by terpenoids and cannabinoids. 
It selectively binds with high affinity to benzodiazepine receptors, thus explaining its 
anxiolytic activity (62). The pharmacology of other Cannabis flavonoids is reviewed 
in ref. 34. 

2. Analysis of Phytocannabinoids 

Instrumental methods are most often used for the identification, classification 
(e.g., fiber type, drug type), and individualization (e.g., source tracing) of Cannabis 
plants and products. Because of the complex chemistry of Cannabis, separation tech- 
niques, such as GC or liquid chromatography, often coupled with MS, are necessary 
for the acquisition of the typical chemical profiles and the sensitive, specific, qualita- 
tive, and/or quantitative (e.g., THC potency) determination of Cannabis constituents. 
However, especially for screening purposes and on-site field testing, noninstrumental 
techniques like thin-layer chromatography (TLC) and color reactions are helpful, too. 



Chemistry of Cannabis Constituents 



41 



Table 8 
Noncannabinoid Phenols 



Compound 


Structure 




AD 


Cannabispiran 


Ri = H, R2 = CH3 


Isocannabispiran 


R-i — CH3 i R2 — H 




Ri 




oh 


Cannabistilbene-I 


f\\ 

Ri = OH, R2 = isoprenyl, R3 = H 




R< = OPHq R-> = OH R.j = OOHq 


LydriildlJlbLlllJcl ic-l 1 


or 

Ri = OCH3, R 2 = OCH3, R 3 = OH 




OCH3 








ho > 


Cannithrene-1 


w 

R 2 

Ri = H, R 2 = OH 


Cannithrene-2 


Ri = OH, R 2 = OCH3 



2.1. Microscopy 

Identifying a plant sample as Cannabis sativa L. is the first step. The botanical 
identification of plant specimens consists of physical examination of the intact plant 



42 



Brenneisen 



morphology and habit (leaf shape, male and female inflorescenses, etc.) followed by 
the microscopical examination of leaves for the presence of cystolith hairs (22,63- 
69). The very abundant trichomes, which are present on the surface of the fruiting and 
flowering tops of Cannabis, are the most characteristic features to be found in the 
microscopic examination of Cannabis products (not liquid Cannabis, hashish oil). 
Sometimes microscopic evidence is still available in smoked Cannabis residues. 

2.2. Color Reactions 

It must be stressed that positive reactions to color tests are only presumptive 
indications of the possible presence of Cannabis products or materials containing 
Cannabis products. A few other materials, often harmless and uncontrolled by na- 
tional legislation or international treaties, may react with similar colors to the test 
reagents. It is mandatory for the laboratory to confirm such results by the use of an 
alternative technique, which should be based on MS (70). The most common color 
spot tests include those developed by Duquenois and its modifications (70-74). A 
study of 270 different plant species and 200 organic compounds has shown that the 
Duquenois-Levine modification is most specific (71). The fast blue B salt test is the 
most common color reaction for the visualization of TLC patterns but may also be 
used as spot test on a filter paper (70). 

2.3. Chromatographic Techniques 

2.3.1. Thin-Layer Chromatography 

One- and two-dimensional TLC is suited for the acquisition of qualitative can- 
nabinoid profiles from plant material (70,73,75,76). Fast blue salt B or BB are used 
for visualization and result in characteristically colored spot patterns (68). For 
quantitation, instrumental TLC coupled to densitometry is necessary. High-pressure 
TLC and overpressured layer chromatography have been developed for the reproduc- 
ible and fast determination and isolation of neutral and acidic cannabinoids (77-79). 

2.3.2. Gas Chromatography, Gas Chromatography /Mass Spectrometry 

GC with flame ionization or MS detection is now the best established method for 
the analysis of Cannabis and its products (25,32,70,77 ,80-92). Derivatization is nec- 
essary (e.g., silylation or methylation) when information about cannabinoid acids, the 
dominating cannabinoids in the plant (see Section 1.1.), is required. The total cannab- 
inoid content, i.e., the amount of neutral cannabinoids plus the neutral cannabinoids 
formed by decarboxylation of the acidic cannabinoids, is determined when the GC 
analysis is performed without derivatization (89). GC/MS is the method of choice for 
creating Cannabis profiles and signatures (chemical fingerprints), a tool for attribut- 
ing the country of origin, the conditions of cultivation (indoor, outdoor), an so on (see 
Chapter 3; refs. 21 and 87). 

2.3.3. High-Performance Liquid Chromatography 

High-performance liquid chromatography makes possible the simultaneous 
determination of neutral and acidic phytocannabinoids without derivatization. Reversed- 
phase columns and preferably solvent programmed gradient systems are required for 
the separation of major and minor cannabinoids and their corresponding acids, e.g., 



Chemistry of Cannabis Constituents 



43 



for chemotyping (CBD-, THC, CBD/THC-type etc.), estimating the age (ratio acidic/ 
neutral cannabinoids) of Cannabis, studying the effect of manufacturing processes 
and storage conditions, batch comparison, or direct quantification of THC in aqueous 
herbal preparations (e.g., Cannabis tea) (81,82,93-98). Detection is usually performed 
by UV (70,80,87,98-101) and diode array photometers (93), as well as by fluores- 
cence, electrochemically (102), and, recently, MS (103). 

2.3.4. Other Techniques 

The applicability of capillary electrochromatography with photodiode array UV 
detection for the analysis of phytocannabinoids has been demonstrated (104). 
Supercritical fluid chromatography coupled to atmospheric pressure chemical ioniza- 
tion/MS is characterized by shorter analysis times than GC or high-performance liq- 
uid chromatography and does not require derivatization (105). 

2.4. DNA Testing 

After a Cannabis sample has been identified and classified, it may become 
important to individualize the specimen for forensic and intelligence purposes (22). 
Tracing the source of origin can be performed on a chemical, e.g., by using chromato- 
graphic-spectroscopic profiles (see also Chapter 3) or a genetic base. For DNA profil- 
ing (22,106-1 10), the following techniques are used: randomly amplified polymorphic 
DNA (111), amplified fragment length polymorphism (112), short tandem repeats 
(113,114), inter-simple sequence repeats (115), internal transcribed spacer II (116), 
and microsatellite markers (117). An overview and description of the different DNA 
testing methods is given in ref. 22. 

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108. Cole, M. D. and Linacre, A. M. T. (2002) The identification of controlled plant drugs 
using phytochemistry and DNA. Curr. Topics Phytochem. 5, 129-140. 

109. Linacre, A. and Thorpe, J. (1998) Detection and identification of cannabis by DNA. 
Forens. Sci. Int. 91, 71-76. 

110. Siniscalco Gigliano, G., Caputo, P., and Cozzolino, S. (1997) Ribosomal DNA analysis 
as a tool for the identification of Cannabis sativa L. specimens of forensic interest. Sci. 
Justice 37, 171-174. 

111. Gillan, R., Cole, M., Linacre, A., Thorpe, J. W., and Watson, N. D. (1995) Comparison of 
Cannabis sativa by random amplification of polymorphic DNA (RAPD) and HPLC of 
cannabinoids: a preliminary study. Sci. Justice 35, 169-177. 

112. Miller Coyle, H., Sutler, G., Abrams, S., et al. (2003) A simple DNA extraction method 
for Marijuana samples used in amplified fragment length polymorphism (AFLP) analy- 
sis. /. Forens. Sci. 48, 343-347. 

113. Hsieh, H. M., Hou, R. J., Tsai, L. C, et al. (2003) A highly polymorphic STR locus in 
Cannabis sativa. Forens. Sci. Int. 131, 53-58. 



Chemistry of Cannabis Constituents 



49 



1 14. Gilmore, S., Peakall, R., and Robertson, J. (2003) Short tandem repeat (STR) DNA mark- 
ers are hypervariable and informative in Cannabis sativa: implications for forensic inves- 
tigations. Forens. Set Int. 131, 65-74. 

115. Kojoma, M., Iida, O., Makino, Y., Sekita, S., and Satake, M. (2002) DNA fingerprinting 
of Cannabis sativa using inter-simple sequence repeat (ISSR) amplification. Planta Med. 
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1 16. Gigliano, G. (1998) Identification of Cannabis sativa L. (Cannabaceae) using restriction 
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Cannabis sativa for DNA typing and genetic relatedness analyses. Anal. Bioanal. Chem. 
376, 1225-1233. 



Chapter 3 



Chemical Fingerprinting 

of Cannabis as a Means of Source 

Identification 

MahmoudA. ElSohly, Donald F. Stanford, 
and Timothy P. Murphy 

1. Introduction 

Marijuana is the most widely abused and readily available illicit drug in the United 
States, with an estimated 11.5 million current users annually purchasing more than 
$10 billion of the drug (I). Drug enforcement agencies are therefore keenly interested 
in trafficking routes of both foreign and domestically grown supplies of marijuana. 
From confidential sources to satellites, these agencies employ a multitude of methods 
to gather intelligence to direct resources, plan control operations, and develop poli- 
cies. A practical means to recognize the source of seized marijuana would be a valu- 
able tool for those purposes. Based on findings from 1990 to 1992 and described here, 
one way to determine origin is by using a chemical fingerprint system, a method that 
has shown promise as an effective intelligence tool to ascertain the geographic origin 
of confiscated marijuana samples. Of the many factors that affect the chemical con- 
stituents of marijuana, it is apparent that environmental factors consistently induce 
profiles unique to each environ. An "environ of origin" as broad as a continent or as 
small as an indoor garden may be differentiated based on the chemical fingerprint, or 
"signature," of marijuana cultivated there — if a statistically significant number of 
samples grown in that environ are available for comparison. However, because all 
environs are not unique, the chemical fingerprint of cannabis is not considered to be 
an ultimate tool for forensic applications, although the technique may effectively sup- 

From: Forensic Science and Medicine: Marijuana and the Cannabinoids 
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey 

57 



52 



ElSohly et al. 



port other types of evidence and is certainly of particular value in intelligence opera- 
tions. 

Scientists have developed sophisticated techniques to study the unique patterns 
of the infinite combinations of chemical compounds making up specific materials and 
have applied those techniques to various disciplines. 

Over some 35 years, a number of researchers have examined the chemical com- 
pounds unique to the Cannabis plant and have consistently reported that the "cannab- 
inoids" are indicative of the country of origin and that environmental factors affect 
cannabinoid profiles. During the 1970s a number of publications appeared that used 
gas chromatography (GC), thin-layer chromatography, and high-performance liquid 
chromatography techniques to compare cannabinoid concentrations of marijuana grown 
in various regions of the world (2-10). In the 1980s and 1990s those technologies 
advanced greatly, and researchers continued to reach similar conclusions (11-19). 
Marijuana from different geographical regions has also been compared using other 
analytical techniques, including elemental analysis (20,21), GC analysis of headspace 
volatiles (22), analysis of free sugars in the plants (23), microscopic examination of 
pollen (24), and even comparison of insect species found in confiscated materials 
(25,26). 

Nearing the 21st century, as technologies further advanced, scientists turned their 
attention to genetic analyses of marijuana and developed techniques very suitable for 
forensic purposes (27-30). Examination of the DNA of marijuana plants now allows 
forensic investigators to identify even minute particles as Cannabis and to determine 
whether a sample is from the drug or the fiber type of the plant. Just as human DNA 
testing has revolutionized criminology, so has the genetic testing of marijuana given 
prosecutors a reliable means to assert that the stash in a defendant's pocket was har- 
vested from the plant found under a grow light in his basement. However, DNA test- 
ing can be expensive and time-consuming and only reflects a plant's lineage, not the 
environment in which it was grown. 

The primary mission of the US Drug Enforcement Administration (DEA) is to 
enforce the US statutes and regulations concerning controlled substances. One part of 
that mission is to manage a national drug intelligence program. To collect, analyze, 
and disseminate intelligence information at federal, state, local, and foreign levels, the 
DEA uses scientific technologies to help gather the pieces of the worldwide puzzle of 
drug trafficking. In 1977, the DEA initiated the Heroin Signature Program to enhance 
the agency's ability to identify the source of heroin seized or purchased within the 
United States. Following the success of that program, a similar program for cocaine 
profiling was set up in 1997, and a methamphetamine profiling program in 1999. In 
the mid-1980s, realizing the potential value of a fully integrated "cannabis fingerprint 
system" including standardized equipment and methods, a database for reference, and 
an automated means to interpret data, officials turned to the scientific community for 
assistance. 

In 1987, the National Institute of Drug Abuse (NIDA) funded a Small Business 
Innovative Research grant submitted by ElSohly Laboratories, Inc. (ELI), to develop 
analytical methodologies that could be used to compare complete chemical finger- 
prints of Cannabis samples of different geographical origins. At that time, the DEA 



Chemical Fingerprinting of Cannabis 



53 



also provided funds to conduct a feasibility study to demonstrate if a practical chemi- 
cal fingerprint system could be developed. In 1988, ELI reported positive results and 
as a result the DEA funded a phase II study (beginning in 1990) to develop a fully 
operational Cannabis fingerprint system and to establish an initial database of mari- 
juana fingerprints from major production regions. The results of the phase II study 
were reported to DEA in 1992 and are summarized in this chapter. 

2. Chemometrics 

Having had many years of experience in analyzing marijuana and considering 
the scientific precedents of others' work on a portion of the chemical fingerprint, we 
determined that GC/mass spectrometry (MS) would be the most appropriate method- 
ology to collect test data. GC/MS instrumentation would provide not only a chemical 
fingerprint of a marijuana sample, but also spectral data, which would aid in the iden- 
tification of each of those components. Law enforcement agencies agreed to provide 
marijuana samples of presumed authenticity specifically chosen to build a useful data- 
base of major production areas. To avoid bias, statistical software was used to analyze 
the data. 

At the time of the phase I study, the science of chemometrics — the application of 
statistics and mathematical methods to chemical data — was a burgeoning field within 
the computer science and analytical chemistry communities. Although standardized 
pattern-matching software was just beginning to become available, an in-house pro- 
gram was developed by ELI personnel to analyze the data. At the conclusion of the 
study an independent chemometrics company, InfoMetrix, was enlisted to evaluate 
the data using various pattern recognition and statistical methods to further validate 
the concept of a turnkey system. Their report in March 1989 stated that, based on 
studies using their own statistical software, the concept was indeed viable, that every 
sample of foreign origin had been correctly classified by country of origin, and that 
every sample of domestic origin had been correctly classified by state of origin. 

For data analysis in the phase II study, we used a commercial version of InfoMetrix 
software — Pirouette®. At this writing, the latest version of Pirouette is marketed as 
their most comprehensive chemometrics software used to discover associations of 
patterns in data and to prepare and use multivariate classification models. Pirouette, 
like all commercial software, has dramatically evolved in the past 15 years, but the 
early version used in the phase II study perfectly suited the requirements at the time, 
including the capability for interlaboratory data sharing. Its graphical interface allowed 
us to view a three-dimensional representation of an unknown sample compared to a 
model and to rotate the image in order to actually see the relationships of the principal 
chemical components. 

Mathematical algorithms such as principal component analysis and hierarchical 
cluster analysis were used to reduce the large complex data sets into comprehensible 
forms (31). The graphic views emphasized the natural groupings in the data and showed 
which variables most strongly influenced those patterns. The basis of the project was 
to first construct a "model," that is, a set of data that represented the chemical finger- 
print of a plant typical of the "class" to which it is assigned, in this case a country, a 



54 



ElSohly et al. 



state, or any other environ to be studied. How well a model actually represented the 
real world was a matter of the quality of the data, which was in turn dependent on the 
quality (authenticity) of the marijuana samples and of the GC/MS analyses. The suc- 
cess of the study hinged on how well the models could be built — a daunting task. 

To validate proposed multivariate models, "training sets" of data known to be 
representative of the various classes were processed. Once Pirouette was trained to 
recognize classes using a K-nearest-neighbor modeling technique (32), data from 
samples of unknown origin could be tested and shown to be either in or not in a certain 
class or perhaps overlapping two or more classes. Based on the amount of variance in 
the model, Pirouette also provided a measure of the probability of the accuracy of the 
results, i.e., a "confidence" value (32). 

3. Chemical Constituents of Cannabis 

Many of the chemical constituents of Cannabis are common to other plants; how- 
ever, cannabinoids are unique to their namesake (33). Of the hundreds of chemicals 
found in Cannabis — and described at length in this book — 175 were used to develop 
the chemical fingerprint system. Of those compounds readily detectable by the meth- 
ods developed in phase I, 46 were positively identified, including 22 monoterpenes or 
sesquiterpenes, 16 cannabinoids, two noncannabinoid phenols, two hydrocarbons, three 
fatty acid esters, and one miscellaneous aromatic compound (see Table 1). The 
remaining 129 compounds were necessarily included because all of the chemical com- 
pounds contribute to the fingerprint, and only the multivariate data analysis software 
could sort out which ones were important to establish relationships and differentiate 
between the classes. 

For the fingerprint system to be of practical use in all laboratories, the methods 
needed to be reproducible and cost-effective, so simple methods using common labo- 
ratory equipment were developed. The methods used in this study have not been vali- 
dated for reproducibility between different laboratories, but because of the simple 
analytical techniques employed we assumed that the methods would be robust and 
that different laboratories could generate similar data in house. Because the finger- 
print chromatograms are so complex, however, it may be difficult to compare data 
generated at different laboratories. Interlaboratory variation in signature analysis is a 
common and vexing problem in this field; for this reason, the DEA has centralized its 
signature programs at a single, specialized laboratory. 

To prepare a sample for GC/MS analysis, the dried plant material was extracted 
with solvent, and then a portion of the extract was diluted with additional solvent to 
produce a test sample ready to be injected into the instrument. Of the compounds 
extractable using that method, only a portion of those were detectable under the par- 
ticular GC/MS conditions used in the study. Although all of the 175 compounds mak- 
ing up the standardized fingerprints could not be specifically identified (even though 
the spectral evidence suggested some possibilities), each was numbered for reference. 

For the study to be complete, however, it was necessary to identify as many of 
the compounds as possible to better grasp the relationships of the chemical finger- 
prints to their environs. Several techniques were employed in order to understand the 
makeup of the chemical fingerprints. 



Chemical Fingerprinting of Cannabis 55 



Table 1 

Chemical Compounds Identified in a Phase II Study 



Compound 


Peak 


Compound 


Peak 


i erpenes 




t i'\ w« W~\ ft I-* 1 w% » I /" 1 £1 

i^annaDinoias 




Allo-arornadenrene 


u 1 


Cannabichromcnc 


1 7 


LX>CM-jDcTgdniULcllc 


J 


v^diiiid.uiciLrd.11 


4R 


p/ _ f 1.-/-7 m r.Rprn a mntpti p 
U (/ till j IJ CI iidlllL/LCllC 


s 

j 


v^dlllldUlCUllldlL/llLHlC 


41 


r/_Ric;ihn1n1 
La, J_j 1 a d U d 1LJ 1 


77 


i (inn q hi c\!cl r\l 
v^dlllldUlC y C1U1 




p-v^dry upny iiciic 




1 'k n n 'i r~\ 1/11 /~\ | 
V^dlllldUlLllOl 


1 u 


I^iir\7r\nn\/1 1 pn p ayiHp 
v^di y L>uny iichc \) a i li u 




V^dlllldUlCloLHH 


07 


rv - (~* p H rp ti p 

La, WCLll C11C 


84 


i^annfihiTiiffin 

V^dlllldUll U.1 dll 


44 


Piirpnmpnp 

V.- U.1 L. U111C11C 


1 53 


Pann o hi crprol 

V^dlllldUl tiCl LJ1 




y-jz,ULiesiiioi 


1 01 

1U1 


V^dlllldDlIlOl 


1 Q 

1 y 


ijupaLoriu L-IirUIIlcIlc 


1 1 9 

1 1Z 


i^diiiidui virdii 


1 f>l 

ID / 


rv - fin ill n p 
La, V^UdlllC 


OJ 


lip n \if\vr\c dnn n hi "Fura n 

-LyCliy LI 1 UCdlllldUllLlI dll 


1 Lf O 


{"tII ainl 

V.J UdlLJl 


1 on 


A^-Tptmh vHrnpnnnahi nol 

i_l 1. C Li dll V Lll UCdlllldUlllUl 


^» 1 


LX>riuiiiuiciic 


o 


za - 1 cLrdiiyurucdiiiidDiiiui 


1 o 


Isoledene 


132 


Tetrahydrocannabinol-^ 


51 


T nnmmlpnp 
HJlltZllUlCllC 


9 


T^f*tT"Qh \ir\ i*/"\ c QnnQni {~\vc\c o 1 
1 CL1 dliy LllUCdlllldLUL/l UCdl 




ri c-^TproliHol 

Lij 1> CI U11UU1 


00 

7a 


Tpf rah uHrorann ahi viran 

1. C LI dll V Lll VJCdlllldUl V 11 dll 


14 


fr^m 1 \|pm 1 1 H c»l 
1 1 till J IN CI U11UU1 


(SO 






Sativene 


O "3 
OJ 


Noncannabinoid phenols 




a-Selinnene 


66 


Cannabispiran 


30 


a-Terpineol 


107 


Dehydrocannabispiran 


58 


Valencene 


152 






a-Zingeberene 


73 


Fatty acid esters 

Palmitic acid methyl ester 


38 


Hydrocarbons 




Oleicacid methyl ester 


56 


Heptacosane 


57 


Linoleic acid methyl ester 


140 


Nonacosane 


21 







Aromatic compounds 

Butylated hydroxytoluene 130 



A 1988 study provided information to identify most of the cannabinoids based 
on retention time and mass spectra (34), but other components were more elusive. 
Because many of the compounds have almost identical mass spectra and can only be 
positively identified by GC/MS using a pure reference standard of that compound to 
establish the retention time on a particular instrument, as many reference standards as 
could be obtained within the scope of the study were analyzed. 

The terpenes were of great interest because their production by plants was likely 
to consistently reflect the immediate environment, whereas the cannabinoids would 
tend to reveal genetic relationships. A commercial GC/MS data library (35) was avail- 
able in both digital and print formats to help identify many of the terpene compounds. 



56 



ElSohly et al. 



4. Experimental Design 

The specific goal of the study was to develop a fully operational fingerprint sys- 
tem that could be used to determine the probability that a particular marijuana sample 
of unknown origin had been grown in one of the target foreign countries or domestic 
states or other environs in the database. The top priority for the experimental design 
was to be able to distinguish between foreign and domestically produced marijuana in 
order to determine the prevalence of foreign material entering the country vs domestic 
material being trafficked. The second objective was to accurately determine the coun- 
try of origin. The third goal was to provide a method to accurately estimate the ratio of 
indoor vs outdoor domestic production. Determination of the state of origin of plants 
grown outdoors in the United States was of lower priority. 

Specimens, or "exhibits," from the various regions known to be major contribu- 
tors to the illicit marijuana market in the United States were submitted by law enforce- 
ment agencies. To ensure the validity of the origins of the specimens, they were shipped 
directly from the areas of collection and were therefore presumed to represent true 
authentics. Both marijuana and hashish specimens were made available for the study. 
Additional specimens cultivated under experimental conditions were produced at the 
NIDA Marijuana Project garden at the University of Mississippi (UM). To maintain 
the integrity of specimens over the length of the study, all were stored in a freezer 
(-20°C) before analysis. Samples were usually analyzed within 4 weeks of preparation. 

Of the 202 marijuana exhibits representing six regions, 157 passed the initial 
quality control (QC) requirements of specimen integrity designed to ensure represen- 
tative fingerprints. To ensure consistency, only mature female plants were included in 
the study. Specimens that could not be determined to be from mature plants (no buds 
or seeds), those in poor condition (molded or decayed), those contaminated with soil, 
and those composed of mostly seeds, stems, and roots but lacking suitable leaf mate- 
rial were rejected. The exhibits from regions included in the phase II database in- 
cluded 26 Colombian, 35 Jamaican, 20 Mexican, 30 Thai, 25 Californian, and 21 
Hawaiian samples. Of course, Hawaiian marijuana was expected to have a fingerprint 
with foreign traits. 

The original study also included 17 exhibits from Tennessee that were not defi- 
nitely mature but were included in the study to provide data from the eastern United 
States. We have chosen to exclude those data here because the profiles of the Tennes- 
see exhibits were shown to be unreliable, which could be related to their stage of 
maturity. The exclusion of these data had no effect on the conclusions of the study. 

Because marijuana grown under controlled conditions was necessary to support 
the fingerprint studies, several growing experiments were carried out at the UM mari- 
juana garden during both phase I and II periods. Second-generation daughter plants 
were grown from seeds collected from 38 phase I exhibits to compare the fingerprints 
of genetically equivalent plants grown outside the country of origin. 

Two experiments were conducted to compare the fingerprints of plants grown 
indoors to those grown outdoors. Twenty cuttings from a Jamaican female plant 
obtained from the US Department of Agriculture Laboratory in Beltsville, MD, were 
grown under three conditions: outdoors in the ground, outdoors in pots, and in pots 



Chemical Fingerprinting of Cannabis 



57 



indoors under artificial lighting. For the second indoor/outdoor experiment, 10 plants 
of a single high-tetrahydrocannabinol-potency variety were grown both indoors in 
pots using commercial potting soil and outdoors in the ground of the University of 
Mississippi marijuana garden. 

To study how the chemical fingerprints of both sexes of marijuana plants vary at 
different stages of plant maturity, leaf samples were collected at regular intervals from 
plants of Mexican origin grown outdoors. Specimens from five male and five female 
plants were analyzed to study how their fingerprints developed at 8, 12, 16, 20, and 25 
weeks of age. 

Because many chemical compounds readily decompose, given time, and because 
the decomposition generally occurs more rapidly at elevated temperatures, a study 
was initiated to determine how fingerprints change during the time between the col- 
lection of exhibits and their transfer to a freezer. For this experiment, 80 specimens 
from the UM garden were stored in paper bags both at room temperature and at an 
elevated temperature and then transferred to a freezer after 30- and 90-day intervals. 

Because of the inherent nature of hashish, a refined product made from the resin 
of Cannabis and intended for commerce, all of the available exhibits were suitable for 
chemical analysis, except that several localities were not represented with a statisti- 
cally significant number of specimens. Of the 73 hashish exhibits from nine countries, 
68 were included in the database: 8 from Afghanistan, 6 from Colombia, 18 from 
India, 10 from Lebanon, and 26 from Pakistan. A recent report indicated lack of ho- 
mogeneity in bars of compressed Cannabis resin (hashish; ref. 36). However, because 
the amount of material received from each sample was small (~5 g), homogenicity of 
each sample was presumed. 

5. Methodology 

5.1. Extraction 

Each marijuana sample was first manicured so that the material became a homo- 
geneous mixture of leaf particles with no seeds or stems. A 100.0 mg portion of the 
sample was transferred to a test tube, and to that tube was added 1.0 mL of the extrac- 
tion solution. The extraction solution was methanol and chloroform mixed in a ratio of 
9:1, in which was dissolved phenanthrene at a concentration of 0.2 mg/mL. Phenan- 
threne served as an internal standard, a chemical not naturally present in cannabis but 
appearing as an isolated peak in the chromatograms for use as both a retention time 
marker and a reference for the calculation of the quantities of the peaks of interest. 
The tube containing the sample and extraction solution was placed in an ultrasonic 
water bath for 15 minutes to break the plant tissue and allow soluble chemicals of 
Cannabis to be dissolved in the extraction solution. The tube was then spun in a cen- 
trifuge to force the plant particles to the bottom so that the resulting clear green solu- 
tion could then be transferred to a screw-capped vial without disturbing the sediment. 
Our experience indicated that extracts would remain stable at low temperature, so 
extracts were stored in a freezer (-20°C) until time for GC/MS analysis. 

Hashish samples were prepared very similarly, with the exception that a 50.0-mg 
portion of each sample was extracted. Because hashish in such small quantities was 



58 



ElSohly et al. 



presumed to be homogeneous, the analytical sample was separated from the bulk sample 
using a razor blade to slice from the inner portion while avoiding the outer part, which 
could have been contaminated or excessively oxidized.To prepare a sample test solu- 
tion suitable for injection into the GC/MS, an extract was removed from the freezer 
and a 0.1-mL aliquot was transferred to another vial, to which was added 0.9 mL of 
methanol. 

5.2. GC/MS Analysis 

The GC/MS system consisted of a Varian 3300 gas chromatograph interfaced to 
a Finnigan 700 ion trap detector mass spectrometer. A 30-m DB-1 fused silica capil- 
lary column (J&W Scientific, Inc.), 0.25 mm OD, 0.25 |im film was used. 

For each run, the column was initially held at 70°C for 1 minute; the temperature 
was then increased to 250°C at the rate of 5°C per minute, then held 25 minutes at the 
final temperature for a total run time of 62 minutes. The injection port was heated to 
200°C and used in the splitless mode with the split valve delayed 30 seconds before 
opening. The interface between the GC and the MS was heated to 250°C. 

The data system used to control the GC/MS and quantitate the peaks in the chro- 
matograms was a desktop PC using Finnigan ITDS 4.10 software. Mass spectral data 
was acquired within the range of 55-450 amu at a rate of 0.5 seconds per scan. After a 
sample was injected, data acquisition automatically started after 5 minutes to allow 
the solvent to pass before peaks of interest began to elute. Although the GC oven 
cycled back to the starting temperature after 62 minutes, data acquisition ended 54 
minutes into the run after the last peak was recorded. 

To ensure that the instrument was operating properly, a QC solution was injected 
after every nine test samples, and the QC chromatogram was examined for integrity. 
A mixture of terpenes, cannabinoids, hydrocarbons, and the internal standard was 
selected for QC to provide a reference of known peaks throughout the entire time of 
the run. The QC sample consisted of a methanolic solution of oc-terpineol (21 |xg/mL), 
oc-terpinene (21 (Xg/mL), (3-caryophylene (21 ixg/mL), allo-aromadendrene (21 (xg/mL), 
nonacosane (83 |J,g/mL), cannabidiol (123 |J,g/mL), cannabinol (124 (xg/mL), A 9 -tet- 
rahydrocannabinol (THC; 41 ixg/mL), and phenanthrene (25 Lxg/mL). Injector and col- 
umn maintenance was performed on a routine schedule to prevent any "memory effect" 
resulting from repeated injections, but no blanks were run between samples. 

Each test sample chromatogram was evaluated for acceptability before data analy- 
sis. If the chromatogram exhibited an unusual baseline or low sensitivity, the injection 
was repeated. The area under each peak was measured using ITDS software in the 
manual mode rather than the automatic mode so that the operator could evaluate each 
of the 175 peaks (plus the internal standard peak) for proper peak shape and to ensure 
correct identity assignments as well. Quantitative values of each peak were automati- 
cally calculated by determining the ratio of the area of the peak to that of the internal 
standard within the same chromatogram and comparing that ratio to that of a standard- 
ized calibration file. 

5.3. Multivariate Data Analysis 

Quantitation files created by ITDS software were converted to ASCII files con- 
taining only the peak numbers (identity assignments) and the quantitative values of 



Chemical Fingerprinting of Cannabis 



59 



each. The ASCII files were downloaded to the Pirouette program (InfoMetrix, Incor- 
porated, Woodinvil, WA) and saved as a compatible file format. 

To analyze the data using the power of Pirouette, first the database of all mari- 
juana exhibits from the four countries and two states was used to construct a model of 
the six classes of fingerprints. The data within the model were examined to ascertain 
similarities and differences of the location classes. Then other models containing only 
80% of the database were constructed, leaving 20% of the samples to be tested against 
the models. Having appropriate models for comparison, the remainder of the proposed 
data analysis experiments were conducted, constructing additional models as neces- 
sary. All results were based on the a K-nearest-neighbor classification method (31). 

6. Results of the Phase II Study 

6.1. Similarities Within the Model 

Within the comparison of the broad classes of domestic vs foreign, all foreign 
exhibits were correctly classified. Only one domestic exhibit, a Hawaiian specimen, 
was misclassified. 

When the domestic exhibits were compared with the four foreign countries, the 
single exhibit discrepant in the domestic vs foreign test was again misclassified, being 
indicated to be from Jamaica. All Jamaican and Mexican exhibits were correctly clas- 
sified, as were 93% of the Thai exhibits and 92% of the Colombian. 

The number of misclassifications increased when the exhibits representing indi- 
vidual states were tested within a six-region model. Of the Hawaiian exhibits, 78% 
were correctly located. The majority of misclassified Hawaiian specimens again looked 
Jamaican. All Californian exhibits were correctly identified. 

6.2. Identification of Unknowns 

Satisfied that the phase II fingerprint data were valid when samples included in 
the model were tested, the system was challenged with specimens not included in the 
model. The random removal of 20% of specimens from the database redefined the 
model and provided "unknowns" for the definitive test of the system. This evaluation 
was repeated five times, each time removing different exhibits and testing those against 
each new model. The results are summarized in Table 2, which shows correct classifi- 
cations vs total unknowns for each of the five rounds of evaluation and the totals of 
the individual rounds. 

Although the results certainly ascertained the viability of the fingerprint system, 
we were still concerned about the source of the errors. To investigate the causes of the 
erroneous predictions, we closely examined the data from a different viewpoint. Pre- 
sented in Table 3 is a matrix chart of the misclassified exhibits showing which loca- 
tions fit the fingerprint more closely than the model of its actual origin. It was evident 
that exhibits within certain regions tended to be misclassified more often than those 
from other locations, but those trends would likely be tempered in a database com- 
posed of more exhibits. Although the distinctive fingerprints of the Hawaiian mari- 
juana improved the classification rates of those exhibits, those differences also 
weakened the domestic model. The majority of California exhibits were known to 
have been grown in the northern part of the state, but the single exhibit from southern 



60 



Table 2 

Correct Classifications of Unknowns 



ElSohly et al. 



Location 


Round 1 


Round 2 Round 3 Round 4 


Round 5 


Total 


Correct (%) 


California 


3/5 


4/5 




5/5 


5/5 


5/5 


22/25 




88 


Hawaii 


4/4 


2/4 




4/4 


3/4 


4/5 


17/21 




81 


Colombia 


6/6 


5/5 




5/5 


5/5 


4/5 


25/26 




96 


Jamaica 


7/7 


7/7 




7/7 


7/7 


7/7 


35/35 




100 


Mexico 


4/4 


A/ A 
4/4 




3/4 


4/4 


4/4 


19/20 






Thailand 


4/6 


6/6 




5/6 


5/6 


6/6 


26/30 




87 


Foreign 














105/111 




95 


Domestic 




— 










39/46 




85 


Total 




— 










144/157 




92 












Table 3 
















Misclassification Matrix 












Number 




Number of exhibits 


misclassified as: 






Ori; 


gin 


tested 


CA 


HI 


COL JAM MEX 


THAI 


Total 




California 


25 










2 


1 


3 




Hawaii 


21 


1 




2 








3 




Colombia 


26 











1 





1 




Jamaica 


35 






















Mexico 


20 


1 













1 




Thailand 


30 


1 





1 


2 




4 




Total 


157 


3 


2 


7 


7 


1 


12 





California had a fingerprint very similar to Mexican marijuana, a not-so-surprising 
misclassification. 

6.3. Indoor vs Outdoor 

For year-round production and to avoid routine surveillance, marijuana growers 
in the United States increasingly prefer to nurture their plants indoors out of sight. An 
added benefit of indoor horticulture is that the grower, rather than Mother Nature, 
controls the environment and can provide ideal lighting and temperature conditions as 
well as exact levels of water and nutrients. Not surprisingly, therefore, the fingerprints 
of plants grown indoors are significantly dissimilar to those of outdoor plants. 

A model consisting of three classes — outdoors in the ground, outdoors in pots 
(commercial potting soil), and indoors (commercial potting soil) — was constructed 
from fingerprints of Jamaican plants grown in the UM facilities. All of those speci- 
mens were then tested against that model. It was found that the fingerprints of the 
indoor plants could be differentiated from their outdoor brethren with 100% accuracy. 
The only misclassifications were within the outdoor group, as those plants with roots 
in the earth were sometimes confused with those in pots, a trend that indicates that 
light and temperature may influence the chemical profiles more than soil conditions. 



Chemical Fingerprinting of Cannabis 



67 



A second indoor/outdoor experiment, which involved high-potency plants, sup- 
ported the previous results, as all of those plants were correctly classified. 

6.4. Daughter Plants Grown in a Different Region 

A most interesting experiment was the test to see how the fingerprints of plants 
from foreign seeds cultivated in Mississippi would fare in the system. Seeds from 
exhibits from Colombia, Jamaica, Mexico, Thailand, and Hawaii were planted out- 
doors at the UM garden. Fingerprints of the resulting plants were tested against the 
model constructed from all of the phase II exhibits. 

Of all the Hawaiian daughter plants, 60% were matched to their home state, 
whereas only 14% of the Thai daughters were recognized. The majority of daughter 
plants (56%) were classified as domestically grown. The high rate of misclassification 
supported original predictions that, although genetic relationships are reflected in the 
fingerprints, the environment has a greater effect on the chemical profiles. 

6.5. Age and Sex 

The original experimental design of the fingerprint study required that all speci- 
mens included in the database be from mature female plants, the type of marijuana 
commonly trafficked in the illicit market. To determine if those criteria were actually 
necessary was the intention of the exercise based on the age and sex of plants. Experi- 
mentally grown specimens of 8 and 12 weeks of age were considered immature, whereas 
those 16, 20, and 25 weeks of age were included in the mature class. An equal number 
of both sexes were included. 

Analysis of the data showed a high rate of correct classification (94%); all the 
misses were among the immature group. Results from the model based on sex 
misclassified 30% of the males but only 8% of the females. 

It appears from these data that the sex of the plant did not contribute as much to 
the fingerprint as did the age of the plant. The maturity of the plants, although not of 
great interest to the intelligence community, was definitely a factor in the accuracy of 
the fingerprint system. Our experience analyzing confiscated marijuana for more than 
30 years shows that the majority of the samples were from mature plants (based on the 
physical examination of the samples). The only exception is those samples seized at 
the growing locations before time to harvest. 

6.6. Storage Conditions 

To determine the effect of storage conditions on chemical fingerprints, sets of 
data were compiled into four models, each having one constant condition and one 
variant condition of the two factors: time and temperature. Samples stored at the two 
temperature levels (80 and 120°F) for the two time intervals (30 and 90 days) were 
tested within those models. 

Samples stored at 80°F were distinct from those stored at 120°F, indicating that 
temperature has a significant effect on the chemical profiles. Those stored at 80°F had 
similar profiles over the two periods, indicating that at the lower temperature the pro- 
files do not change over a period of at least 3 months. Samples stored at 120°F for 30 
days, however, could easily be differentiated from those stored for 90 days. 



62 



ElSohly et al. 



6.7. Application of the Marijuana Fingerprint System to Analysis 
of Hashish Samples 

The fingerprints of hashish exhibits are expected to differ greatly from those of 
marijuana because hashish is a product of Cannabis processed to concentrate the 
cannabinoids, primarily THC. For this study the GC/MS data of the hashish samples 
were obtained using the same fingerprint template developed for marijuana, not a new 
set of chromatographic peaks specific to the typical hashish profile. 

Five countries were represented in the 68 hashish exhibits provided for the study, 
but only three broad regions: South America (Colombia), the Middle East (Lebanon), 
and Southwest Asia (Afghanistan, India, and Pakistan). A model based on the five 
countries produced correct classifications at rates of 67% Colombia, 100% Lebanon, 
50% Afghanistan, 67% India, and 73% Pakistan. Because it was noted that the 
misclassified Afghan, Indian, and Pakistani exhibits all fell in the other Asian classes, 
those countries were combined, and a second model was created with South America, 
Middle East, and Southwest Asia as the classes. In the second model, Southwest Asia 
had 98% correct hits, whereas Colombia and Lebanon were 67 and 100%, respec- 
tively, leading us to postulate that the manufacturing methods particular to a region 
may induce distinct differences in the chemical profiles of hashish. The anomalies in 
the Colombian samples were attributed to the small number of available exhibits. 

Although the Cannabis fingerprint system as designed for marijuana reliably 
determined the origins of hashish samples, a fingerprint based on the actual peaks 
found in hashish chromatograms would undoubtedly improve the accuracy. Addition- 
ally, a study of a marijuana profile compared with the profile of hashish made from 
that same marijuana could offer insight into the design of a hashish database. 

6.8. Examination of Chemical Profiles for Distinguishing Peaks 
Characteristic of Specific Regions 

To determine if certain chemical "marker" compounds could be present in mari- 
juana plants from one region, but absent in plants from another region, data were 
again crunched, and Pirouette offered some likely candidates to test this so-called 
silver bullet theory. 

Three sesquiterpenes — peak 70, peak 92, and peak 63 — were predominantly found 
in domestic fingerprints. Peak 70 was present in 54% of the domestic specimens and 
absent in the foreign ones, peak 92 in 90% of the domestic and 13% of the foreign, and 
peak 63 in 93% domestic and 14% foreign specimens. Peak 92 was identified as cis- 
nerolidol, but the others were only tentatively identified because reference standards 
for those compounds could not be obtained. Mass spectral evidence suggested that 
peak 63 was y-elmene and peak 70 either a- or y-gurjunene. 

Peak 130, identified as butylated hydroxytoluene, was detected only in foreign 
specimens, particularly Jamaican, but never in domestic ones. A sesquiterpene, peak 
86, possibly y-cadinene or (3-farnesene, was totally absent from Colombian, Jamaican, 
and Mexican fingerprints but was detected in more than 50% of the Thai and some 
domestic profiles. Peak 100, a sesquiterpene identified as guaiol, was detected in only 
a few Californian, Hawaiian, and Mexican specimens. 



Chemical Fingerprinting of Cannabis 63 

Table 4 
Possible Marker Compounds 

Compound Presence indicates 



c/s-Nerolidol 

y-Elemene" 

a- or y-Gurjunene" 

Butylated hydroxytoluene 

y-Cadinene or (3-farnesene" 

Guaiol 



Domestic 
Domestic 
Domestic 

Foreign (likely Jamaica) 
Thailand (or possibly domestic) 
California, Hawaii, or Mexico 



"Tentative identification. 



Individual compounds that could possibly be used as markers for indication of 
origin are summarized in Table 4. 



7. Conclusions 

It is concluded from this work that chemical profiles of Cannabis samples could 
be used to determine the geographic origin of the samples provided that a database is 
available that has been established with profiles of samples of known origin. The pre- 
dictions that specimens from mature female plants would yield the most consistent 
data and that specimens should be protected from elevated temperatures were con- 
firmed, as was the likelihood that certain chemical compounds, particularly terpenes, 
contributed the most evidence of geographic origin. 

Having in hand a fully functional Cannabis fingerprint system that could readily 
be utilized to gather trafficking data, the goals of the study were realized. The system 
provided a means to distinguish foreign grown marijuana from that grown domesti- 
cally as well as to distinguish plants grown indoors from those grown outdoors. The 
system could also reliably determine the foreign sources of seizures of both marijuana 
and hashish. 

The reliability of the system and its utility is expected to be more in the area of 
intelligence than for forensic purposes. The techniques developed for the fingerprint 
system could, however, be applied in certain forensic situations, where the analysis of 
the multiple constituents of a marijuana sample could rule out the possible sources of 
origin, but not to definitively determine a specific source. 

Although the system did not correctly classify every single specimen, it did show 
the possibility that one could confidently reveal trends of both worldwide and domes- 
tic drug sources. For the system to remain useful over time, the database would need 
to be updated at regular intervals with high-quality authentic samples that reflect cur- 
rent trends in marijuana production. 

Following the phase II studies, agencies in the United States and abroad expressed 
interest in a Cannabis fingerprint system. In 1998, UM licensed the Cannabis finger- 
print methodologies to the Kentucky State Police in support of their Marijuana Signa- 
ture Laboratory, part of intelligence operations focused on certain trafficking areas in 
Kentucky, Tennessee, and West Virginia known as the Appalachia HIDTA (high- 
intensity drug trafficking areas). 



64 



ElSohly et al. 



Since the completion of this work, others have reported on the use of other tech- 
niques for chromatographic profiling of Cannabis and hashish to a very limited extent 
(37,38). Interest in the fingerprint system continues today. For example, colleagues at 
the University of Bern, Switzerland, have recently completed a project to use Pirou- 
ette software to determine any geographical correlations in Cannabis fingerprints of 
various origins. In a report to the Swiss Federal Office of Public Health in 2004, they 
concluded that a Cannabis fingerprint system could effectively determine the source 
of marijuana found within Switzerland (39). 

A CKNOWLEDGMENTS 

The authors wish to acknowledge Dr. P. Tobin Maginnis, Associate Professor of 
Computer and Information Science at the University of Mississippi, who orchestrated 
our data analysis systems. We also wish to thank the Drug Enforcement Administra- 
tion and the National Institute on Drug Abuse, which provided both the impetus and 
the funding for these studies. 

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3. Small, E., Beckstead, H. D., and Chan, A. (1975) The evolution of cannabinoid phenotype 
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4. Steinberg, S., Offermeier, J., Field, B. I., and Jansen Van Ryssen, F. W. (1975) Investiga- 
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5. De Faubert Maunder, J. G. (1970) A comparative evaluation of the delta-9-tetrahydrocan- 
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7. Novotny, M., Lee, M. L., and Low, C. E. (1976) Analysis of marihuana samples from 
different origins by high resolution gas chromatography for forensic application. Anal. 
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8. Wheals, B. B. (1976) Forensic applications of high pressure liquid chromatography. Chro- 
matography 122, 85-105. 

9. Baker, P. B. and Fowler, R. (1978) Analytical aspects of the chemistry of cannabis. Proc. 
Anal. Div. Chem. Soc. 15(12), 347-349. 

10. Tucker, R. B. and Graham, B. F. (1979) Cannabinoid content of a stand of cannabis grown 
clandestinely in Nova Scotia. J. Can. Soc. Forensic Sci. 12(4), 163-172. 

11. Baker, P. B., Fowler, R., Bagon, K. R., and Gough, T. A. (1980) Determination of the 
distribution of cannabinoids in cannabis resin using high performance liquid chromatogra- 
phy. /. Anal. Toxicol. 4(3), 145-152. 

12. Baker, P. B., Gough, T. A., and Taylor, B. J. (1980) Illicitly imported cannabis products: 
some physical and chemical features indicative of their origin. Bull. Narc. 32(2), 31-40. 

13. Baker, P. B., Bagon, K. R., and Gough, T. A. (1980) Variation in the THC content of 
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14. Hemphill, J. K., Turner, J. C, and Mahlberg, P. G. (1980) Cannabinoid content of indi- 
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15. Baker, P. B., Gough, T. A., and Taylor, B. J. (1982) The physical and chemical features of 
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seeds of known origin. Bull. Narc. 34(1), 27-36. 

16. Idilbi, M. M., Huvenne, J. P., Fleury, G., Tran Van Ky, P., Muller, P. H., and Moschetto, 
Y. (1985) Hashish analysis using gas chromatography coupled to fourier transform infra- 
red spectroscopy. II. Tetrahyrocannabinol determiniation. Bull. Soc. Pharm. Lille 41(4), 
33-35. 

17. Nakahara, Y. and Tanak, K. (1988) Studies on discrimination of confiscated cannabis prod- 
ucts by high performance liquid chromatography with electrochemical detector. Bull. Natl. 
Inst. Hyg. Sci. 106, 1 1-88. 

18. Gough, T. A. (1991) The examination of drugs in smuggling offences, in The Analysis of 
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19. Pitts, J. E., Neal, J. D. and Gough, T. A. (1992) Some features of cannabis plants grown in 
the United Kingdom from seeds of known origin. J. Pharm. Pharmacol. 44(12), 947-951. 

20. Fagioli, F., Locatelli, C., Scanavini, L., Landi, S., and Donini, G. B. (1986) Characteriza- 
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21. Watling, R. J. (1998) Sourcing the provenance of cannabis crops using inter-element asso- 
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22. Hood, L. V. S. and Barry, G. T. (1978) Headspace volatiles of marihuana and hashish: gas 
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23. Krishnamurty, H. G. and Kaushal, R. (1976) Free sugars and cyclitols of Indian marijuana 
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24. Bryant, V. M., Jones, J. G., and Midenhall, D. C. (1990) Forensic palynology in the United 
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25. Crosby, T. K, Watt, J. C, Kistemaker, A. C, and Nelson, P. E. (1986) Entomological 
identification of the origin of imported cannabis. /. Forensic Sci. Soc. 26(1), 35-44. 

26. Smith, K. G. V. (ed.) (1986) Cannabis insects, in A Manual of Forensic Entomology, 
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27. Gilmore, S., Peakall, R., and Robertson, J. (2003) Short tandem repeat (STR) DNA mark- 
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28. Miller, C. H., Palmbach, T., Juliano, N., Ladd, C, and Lee, H. C. (2003) An overview of 
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29. Hsieh, H. M., Hou, R. J., Chen, K. F., et al. (2004) Establishing the rDNA IGS signature of 
Cannabis sativa. J. Forensic Sci. 49(3), 477-480. 

30. Gigliano, G. S. and Finizio, A. D. (1997/1998) The Cannabis sativa L. fingerprint as a tool 
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34. Brenneisen, R. and ElSohly, M. A. (1988) Chromatographic and spectroscopic profiles of 
Cannabis of different origins: Part I. /. Forensic Sci. 33(6), 1385-1404. 

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37. Lehmann, T. and Brenneisen, R. (1995) High performance liquid chromatographic profil- 
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land. 



Chapter 4 



Marijuana Smoke Condensate 

Chemistry and Pharmacology 

Hala N. ElSohly and Mahmoud A. ElSohly 

1. Introduction 

Cannabis sativa is one of the oldest plants known to medicine and one of the 
most thoroughly studied plants today. Much knowledge has been gained about the 
chemistry, pharmacology, metabolism, and pharmacokinetics of pure compounds from 
Cannabis, as well as the chemical and biological analysis of marijuana smoke con- 
densate (MSC). In this chapter, we review data related to the preparation of MSC, the 
composition and analysis of MSC, and the pharmacological and toxicological effects 
of MSC. 

2. Preparation of Marijuana Smoke Condensate 

Patel and Gori (1) described the preparation of marijuana cigarettes and the pro- 
duction of MSC. Various analytical parameters of blended marijuana (i.e., ash, hex- 
ane solubles, nitrate, reducing sugars, citric acid, malic acid, oxalic acid, potassium, 
sodium, calcium, magnesium, cadmium, chromium, and A 9 -tetrahydrocannabinol 
[THC]) and marijuana cigarettes (average weight, average moisture content, static 
burning rate, fire zone temperature at 15- and 55-mm marks) were determined. 

2.1. Production of Smoke Condensate 

The cigarettes to be smoked were first conditioned at 24 ± 1°C and 60 + 5% 
relative humidity. The average weight of a marijuana cigarette was 1.1 g. The smok- 
ing machine used was designed to automatically load, light, smoke, and eject approx 
2000 cigarettes per hour and take a maximum of 10 puffs per cigarette at the rate of 

From: Forensic Science and Medicine: Marijuana and the Cannabinoids 
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey 

67 



68 



ElSohly and ElSohly 



one puff per minute. The smoke condensate-trapping system consisted of four 3-L 
Pyrex reaction flasks with Teflon® covers, glass and Teflon interconnecting piping, 
and a leak-tight stainless steel tank with metal support for flasks. The assembled traps 
were housed in a refrigerated cabinet capable of sustained operation down to -30°F. 
The traps were further cooled down to -90°F by immersion in a slurry of dry ice and 
isopropanol. The condensate from the trapping system was extracted with acetone and 
concentrated in vacuo (<40°C) to yield a smoke condensate sample with less than 5% 
water. The mean dry smoke condensate yield was 9.37 ± 1.05 (mg/cigarette). Analysis 
of cannabinoids in the smoke condensate was carried out by gas chromatography/ 
flame ionization detection (GC/FID) (2) using a packed column (6 ft x 2 mm, 3% OV- 
17 on 180-120 mesh Gas-Chrom Q). The mean percentage (n = 8) of A 9 -THC, canna- 
bidiol, and cannabinol in the smoke condensate was 3.63 ± 0.15, 1.95 ± 0.13, and 1.87 
± 0.08, respectively. 

Sparacino et al. (3) prepared cigarettes from Mexican marijuana containing 1.3% 
A"-THC (labeled as low dose) and 4.4% A 9 -THC (labeled as high dose) using low- 
porosity "street" cigarette papers. Standard research tobacco cigarettes were also pre- 
pared. Marijuana and tobacco cigarettes were used to generate smoke condensates 
under constant draft or intermittent puff smoking modes. The evaluation of smoke 
condensates from these two systems would provide a qualitative and quantitative range 
within which the various components of the marijuana smoke actually experienced by 
human smokers might be found. The cigarette smoking was conducted at flow rates of 
1200 mL per minute for all constant draft combustion runs, 40 mL per 2-second puff 
(one puff per minute) for puff mode combustion runs with marijuana, and 35 mL per 
2-second puff (one puff per minute) for puff mode combustion runs with tobacco ciga- 
rettes. Six smoke condensates were generated: MSC — low potency by puff and con- 
stant draft mode; MSC — high potency by puff and by constant draft; and tobacco 
smoke condensate by puff and by constant draft. 

3. Fractionation and Analysis of Marijuana Smoke Condensate 

MSC is a highly complex matrix containing several thousand compounds that 
may vary over several orders of magnitude (4). A liquid-liquid fractionation scheme 
(5,6) allowed the separation of these components into different classes of compounds 
(i.e., acidic, basic, and neutral: nonpolar, polar, and polyaromatic hydrocarbons; see 
Fig. 1). 

In 1975, Jones and Foote (7) reported acids, phenols, and bases that were chemi- 
cally separated from the smoke condensate of 2638 marijuana cigarettes and semi- 
quantitatively analyzed by GC and GC/mass spectrometry (MS). The analysis of the 
basic fraction (1.47 g, 4.8% of total MSC hydrochlorides) was carried out by GC/FID 
using a packed column (10 ft. x V 8 in., 28% Pennwalt 223 + 4% KOH on chromosorb 
R, 80-100 mesh). While no fore-column was used for the GC/MS analysis, a glass 
fore-column was used for GC/MS analysis with the first 2 in. packed with powdered 
soda lime to liberate the amines and the remaining 5 in. packed with ascarite to absorb 
water. The phenolic fraction (0.96 g, 4.6% of total MSC) was analyzed as the TMS 
derivative by GC/thermal conductivity detector using a packed column (5% OV-17 on 
Diatoport S, 60-80 mesh). The acidic fraction (1.57g, 7.5% of total MSC) was esteri- 



Marijuana Smoke Condensate 



69 



Smoke Condensate 



i. Dissolve in methylene chloride 

ii. Partition with an equal volume of sodium 
hydroxide (1M) 

iii. Separate phases 



Methylene chloride 



i. Wash with hydrochloric acid (0.2M) 

ii. Separate phases 



Aqueous basic fraction 

i. Acidify 

ii. Extract with methylene 
chloride 



Acidic fraction 



Methylene chloride 
Evaporate 



Aqueous acidic layer 
i. Basify 



Residue 



ii. Extract with methylene chloride 

iii. Evaporate 
Basic fraction 

Partition between cyclohexane 
and methanol/H 2 



Methanol/H 2 
Polar neutral fraction 



Cyclohexane 

i. Concentrate 

ii. Wash with nitromethane 



Cyclohexane 
Non-polar neutral fraction 



Nitromethane 
Polynuclear aromatic hydrocarbon fraction 



Fig. 1. Fractionation scheme for marijuana smoke condensate. 



fied with boron trifluoride-methanol (BF 3 -MeOH, 14%, V/V) to the corresponding 
methyl esters and analyzed by GC/FID using a packed column (2% OV-17 on Gas- 
Chrom Q, 80-100 mesh). The neutral fraction (17.4 g, 83.1% of the total MSC) was 
not analyzed. 

Van Den Bosch et al. (8) reported on the constituents of MSC generated from 
640 cigarettes hand-rolled from Mexican marijuana (A 9 -THC content 1.29%). The 
condensate was fractionated into basic (0.3 g), phenolic (1.6 g), acidic (0.3 g), and 
neutral (6.9 g) fractions. The neutral fraction was further purified by column chroma- 
tography using silica gel and a step-gradient mobile phase consisting of n-hexane, n- 
hexane-benzene, benzene, ether, and methanol. The different fractions were analyzed 
by GC and GC/MS using a glass column (200 x 3 mm id) packed with 3% OV-17 on 
chrompak SA (80-100 mesh) or a glass capillary column containing OV-101. 

Zamir-ul Haq et al. (9) identified and quantitatively determined the Af-heterocy- 
clic carbazole, indole, and skatole in MSC using GC, MS, and liquid scintillation 
spectrometry. The dry condensate was partitioned between hexane and methanol/wa- 
ter. The hexane fraction was subjected to column chromatography to yield a fraction 
enriched in the above-mentioned compounds. Qualitative analysis was carried out by 
GC/FID/MS using a glass column (6 ft x 2 mm) packed with 3% Silar 5CP on Gas 



70 



ElSohly and ElSohly 



Chrom Q. For the quantitative analysis, separate experiments were done using indi- 
vidual radiolabeled carbazole, indole, and skatole as internal standards. The opera- 
tional losses of carbazole, indole, and skatole were quite different from each other, 
and thus none of the internal standards could be used for the quantitation of the other 
components. The average amounts of carbazole, indole, and skatole were 89 ± 3, 826 
± 4, and 597 ± 7 [ig/g of fresh condensate, respectively. The effect of aging of the 
condensate was studied by analysis of a composite of all samples collected every 8 
weeks for 2 years. The data showed a decrease in the levels of carbazole and indole, 
whereas levels of skatole increased on standing. 

The previously described solvent partition method (Fig. 1; ref. 6) was used by 
Merli et al. (10) to separate the basic fraction of Mexican MSC. Enrichment of some 
trace components was accomplished with high-performance liquid chromatography on 
an aminosilane-bonded Porasil C (11). The analysis of this fraction was carried out by 
capillary GC/MS using a glass capillary column (50 m x 0.25 mm id) etched with gas- 
eous HC1 at 400°C and statically coated with UCON 50-HB-2000 stationary phase. 
Kalignost or benzyltriphenyl phosphonium chloride was added directly to the stationary 
phase solution in order to form a 10% addition to the amount of polymer phase used. 
The method allowed the identification of more than 300 nitrogen-containing compounds. 
The authors pointed to the fact that certain compounds of the hydrogen-donor nature, 
e.g., indole and carbazole derivatives, may end up in the polar neutral fraction (12) 
while using this solvent partitioning scheme. In addition, the comparison of MSC with 
that of tobacco (prepared and characterized by the same methodology) revealed that 
there are both qualitative and quantitative differences between the two condensates. 

Further analysis of the basic fraction of marijuana and tobacco smoke conden- 
sates was carried out by Novotny et al. (13) using capillary GC/MS. The use of ther- 
mostable Superox-coated glass capillary column (Superox-4, 15 m x 0.25 mm id) 
allowed for the elution of relatively large nitrogen-containing compounds. The use of 
short columns allowed the elution of larger nitrogen-containing molecules in a rea- 
sonable time without sacrificing the peak resolution needed for the subsequent mass 
spectral investigations. Marijuana and tobacco smoke condensates showed qualitative 
similarities with a number of alkylated pyridine and quinoline derivatives, aza-in- 
doles, and aza-carbazoles; however, quantities of these components in both conden- 
sates were quite different. 

Sparicino et al. (3) analyzed the strongly mutagenic fraction of MSC, produced 
from high-dose marijuana (A 9 -THC, 4.4%) under constant draft mode, by GC/MS. A 
capillary column (60 m, packed with DB-1701) was used. Approximately 200 com- 
pounds were identified. About half of this total were amines; with about half of these 
being aromatic amines. Pyrazines, pyrimidines, pyrroles, pyridines, and isoxazoles 
were the predominant compound classes. Some alkylated pyrazoles and pyrazines, as 
well as an alkylated benzimidazole, were detected in very large amounts. 

Chemical ionization/MS was used to quantify noncannabinoid phenols in MSC 
( 14 ). The methylene chloride-soluble material of the smoke condensate generated from 
100 cigarettes prepared from female Mexican marijuana was fractionated between 
saturated aqueous sodium bicarbonate and then with 0. 1 N aqueous sodium hydroxide 
solution. The aqueous sodium bicarbonate and sodium hydroxide solutions were acidi- 



Marijuana Smoke Condensate 



71 



fied, extracted with ether, and analyzed as their TMS derivatives. A stainless steel 
column (3 m, 1% OV-17 on 100/120 mesh Gas-Chrom Q) and FID were used. 

A capillary GC/MS method was developed by Maskarinec et al. (15) for the 
analysis of organic acids and phenols in MSC. The methodology used consisted of 
solvent partitioning (6), selective fraction enrichment by gel chromatography, fol- 
lowed by conversion of sample components to volatile methyl ester/ether derivatives 
for GC. A glass capillary column (20 m x 0.25 mm id) coated with free fatty acid 
phase was used, and it provided adequate resolution required for the MS investigation 
of the sample components. GC profiles of the acidic fractions obtained from Mexican 
(100 cigarettes, A 9 -THC, 2.8%; 6.25 mg acid/cigarette) and Turkish marijuana (100 
cigarettes, A 9 -THC, 0.3%) and standard tobacco (prepared from equal weight, 2.05 mg 
acid/cigarette) smoke condensates were compared and indicated both qualitative and 
quantitative changes in the constituents of chromatographic profiles. Forty-nine com- 
ponents were identified in the acidic fraction of Mexican MSC. 

Analysis of the polynuclear aromatic hydrocarbon fraction (see Fig. 1 ; ref. 6) of 
marijuana and tobacco smoke condensates was carried out with a combination of chro- 
matographic and spectral methods (16). Selective enriched extracts were further puri- 
fied by liquid chromatographic methods and analyzed by capillary GC/MS using a 
capillary column (1 1 m x 0.26 mm id) coated with SE-52 methyl phenyl silicone as a 
stationary phase. Approximately 150 polynuclear compounds in each smoke material 
type were quantitated and tentatively identified as to parent ring structures and type of 
alkyl substituents. Further identification of methyl derivatives of polynuclear aromatic 
hydrocarbons in air particulates, tobacco, and MSCs was accomplished by chromato- 
graphic separation into fractions of similar ring types and analysis using nuclear mag- 
netic resonance (17). The positions of substitution in the rings were identified 
from the methyl chemical shifts. For the lower relative molecular mass fractions 
of anthracene-phenanthrene and fluoranthene-pyrene, the smaller number of methyl 
derivatives made identification possible from nuclear magnetic resonance alone. For 
mixtures containing benz [a] anthracene and chrysene derivatives, additional GC/MS 
was required. Overnight accumulation of Fourier transform spectra allowed approx 
20-txg amounts of single constituents to be measured in 0.5- to 1.5-mg fractions. 

The analysis of the neutral constituents (polar and nonpolar) of the smoke con- 
densates of Mexican marijuana and standard tobacco (obtained according to Fig. 1) 
was carried out using GC/MS (18). Because the constituents of the polar neutral frac- 
tion were mostly nonvolatile, silylation facilitated a partial characterization of this 
fraction. A glass capillary column (50 m x 0.25 mm id) coated with OV-101 methyl 
silicone fluid was used. In total, more than 130 neutral smoke components were char- 
acterized. It is to be pointed out that the comparison of the chromatographic profiles 
of the nonpolar fractions for marijuana and tobacco indicated some similarities, but 
also qualitative and quantitative differences in their terpenic compositions. The authors 
noted that peaks eluting in the temperature range of 120-160°C represent fairly unique 
components of marijuana smoke. Terpenes of these and similar structures have previ- 
ously been found in the unburned marijuana samples (19) and are believed to be 
responsible for the characteristic odor of marijuana and its smoke. The components of 
the polar neutral fraction of both marijuana and tobacco smoke condensates revealed 



72 



ElSohly and ElSohly 



considerable similarity between the two materials. The only notable differences are 
the expected presence of nicotine and main cannabinoids in tobacco and marijuana 
smoke, respectively. The profiles of phenolic substances in tobacco and marijuana 
were qualitatively and quantitatively similar. A summary of the acidic, phenolic, non- 
polar neutral, polar neutral and polynuclear aromatic hydrocarbons is presented in 
Table 1. 

4. Pharmacological and Toxicologic al Activities 

4. 1 . Be ha vioral A ctivity 

Whole smoke condensate from female Mexican marijuana was solvent-fraction- 
ated into four fractions using pentane, ether, methylene chloride, and ethanol. These 
fractions were tested in the rat (iv via leg or tail veins) for spontaneous posture, cata- 
tonic, locomotion, and coordination as well as evoked responses of arousal, startle, 
vocalization, and biting. The smoke condensate of marijuana (6 mg/mL, 0.44 mg/mL 
of A 9 -THC) and the pentane fraction (3 mg/mL, 0.5 mg/mL of A 9 -THC) had less 
behavioral effects in the rat than the corresponding amounts of A 9 -THC contained in 
those extracts. The EtOH extract (2 mg/mL, <0.04 mg/mL A 9 -THC) had behavioral 
effects in two or three depressant parameters, and these effects were enhanced by the 
addition of A 9 -THC. The methylene chloride (2 mg/mL, <0.04 mg/mL A 9 -THC) showed 
no behavioral activity when given alone, but produced with added A 9 -THC an en- 
hanced catatonic effect and decreased the provoked bite effect that A 9 -THC produces. 
It was concluded (21) that the various fractions of MSC produced behavioral effects 
in the absence of A 9 -THC. Subsequently, a study (22) was carried out on the pharma- 
cological activity of the acidic, basic, and polar-neutral fractions of marijuana whole 
smoke condensate alone and in combination with A 9 -THC. Male Swiss-Webster mice 
were used for all studies, and all administrations were via the tail vein. The acidic frac- 
tion was essentially inactive in a general activity screen at doses of 5 and 25 mg/kg. A 
dose of 125 mg/kg caused a nonspecific depression of behavioral and neurological 
parameters with little effect on autonomic function. The basic fraction also showed 
little activity in a general pharmacological screen at doses of 5, 10, and 20 mg/kg. 
Incidence of defecation and urination was also reduced at doses of 17 and 29 mg/kg. 
The polar-neutral fraction lowered body position, impaired motor coordination, and 
induced hypothermia at 30 and 60 minutes postinjection at a dose of 200 mg/kg. Both 
the acidic and polar-neutral fractions altered the activity of A 9 -THC when adminis- 
tered with that compound. Doses of 5.6 mg/kg acidic fraction and 7.4 mg/kg polar- 
neutral fraction prolonged the hypothermia induced by 1 mg/kg A 9 -THC, while not 
affecting body temperature when administered alone. The basic fraction, however, 
did not alter body temperature when given alone or in combination with A 9 -THC. A 
subsequent study on the basic fraction of MSC obtained from Mexican marijuana (0.8% 
A 9 -THC) was evaluated in mice (23) looking at behavioral, neurological, and auto- 
nomic effects. This fraction administered by intravenous route (tail vein) at doses of 
5,10, and 20 mg/kg caused impairment of visual placing, increase in tail pinch response, 
decrease in tail evaluation, and induction of piloerection. These effects, although sta- 
tistically significant, were slight and not consistently dose dependent. In doses rang- 



Marijuana Smoke Condensate 



73 



Table 1 

Basic, Acidic, Phenolic, Nonpolar Neutral, Polar Neutral and Polynuclear Aromatic 
Hydrocarbons Present in Marijuana Smoke Condensate 



Class of compounds 



Amount 



Ref. Present in tobacco smoke? 



Basic 

Dimethylamine 

Piperidine 

Pyridine 

2- Methylpyridine 
Pyrrole 

3- (and/or 4-)Methylpyridine + 

dimethylpyridine 
Two dimethyl- or ethylpyridines 
One trimethyl-, methyl ethyl-, or 

propylpyridine 
Quinoline 
Methylpyrazine 
2 ,5 -Dime thy lpyrazine 
2,6-Dimethylpyrazine 
Methyl ethyl pyrazine 
One dimethyl-, diethyl-, 

methylpropyl-, or butylpyrazine 
Norharman 
Harman 
Carbazole 



Indole" 



Skatole 



Dimethylamino acetonitrile 
Methylpyrimidine 
2,6-Dimethylpyridine 
3 -Methylpyridine 
Dimethyl- or ethylthiazole or 

-isothiazole (2 isomers) 
4-Methylpyridine 
2-Ethylpyridine 
Dimethyl-, ethy lpyrazine or 

-pyrimidine (3 isomers) 
Trimethyl-, ethyl methyl-, or 

propyl pyridine (20 isomers) 
2,5-Dimethyl pyridine 



4% 

2% 

43% 

16% 

2% 

18% 



7 

7 
7,10 
7,10 

7 

7 

8,10 
8,13 

8,13 
3,8,10 
8 
8 

3,8,10 
3,8 



89 ± 3 ixg/g 
of fresh 
condensate 

826 ± 4 fig/g 
of fresh 
condensate 

597 ± 7 jig/g 
of fresh 
condensate 



8 



9,16 



9,18 



10 
3,10 
10 
10 
10 

10 
10 
10 

10,13 

10 



No 
No 
Yes 
Yes 



No 
No 



Yes 
No 
Yes 
Yes 
Yes 

Yes 
Yes 
No 

Yes 

Yes 



(continued) 



74 



ElSohly and ElSohly 



Table 1 (continued) 



Class of compounds 



Amount 



Ref. Present in tobacco smoke? 



2.4- Dimethyl pyridine 

2.3- Dimethyl pyridine 

3 - Ethyl pyridine 

2- Vinyl pyridine 

4- Ethyl pyridine 

Trimethyl- or methylethylthiazole 

or isothiazole 
Trimethyl or methyl ethyl pyrazine 

or pyrimidines (4 isomers) 
Trimethyl pyrimidines 
Methyl ethyl pyrimidines 
Butyl-, methyl propyl-, diethyl-, 

ethyldimethyl-, or 

tetramethylpyridine (33 isomers) 

3.5- Dimethylpyridine 
Propyl-, methyl ethyl-, or 

trimethylpyrazole or -imidaole 
(15 isomers) 

3 - Vinyl pyridine 

3 .4- Dimethylpyridine 

Methyl vinyl- or propenyl pyridine, 

or azaindan 
Butyl-, methyl propyl-, diethyl-, 

diethylmethyl-, or 

tetramethylpyridine or 

-pyrazine (5 isomers) 
Alkylpyridine with five or more 

carbon atoms in saturated side 

chains (45 isomers) 
Butyl-, methyl propyl-, diethyl-, 

dimethylethyl-, or 

tetramethylpyrazole or 

-imidazole (16 isomers) 
3 -Methoxypy ridine 
2-Acetylpyridine 
jV-Furfurylpyrrolidine (?) 
Methylmethoxypyridine 

4- Methylthio-2-butanone (?) 
Methylacetylpyridine (4 isomers) 
1 -Methylimidazole 

Furfuryl alcohol 
Ethylvinyl-, dimethylvinyl-, 

methylpropenyl-, or 

methyl azaindan or 

tetrahydronaphthalene (35 isomers) 



10 
10 
10 
3,10 
10 
10 

10 

10 
10 
10 



10 
3,10,13 



10,13 
7,10 
10,13 

10 



10 



3,10 



10 
3,10 

10 

10 

10 
10,13 
3,10 
10,13 
10,13 



Yes 
Yes 
Yes 
Yes 
Yes 
No 

Yes 

Yes 
Yes 
Yes 



Yes 
Yes 



Yes 
Yes 
Yes 

Yes 



Yes 



No 



Yes 
Yes 
Yes 
No 
No 
Yes 
No 
Yes 
Yes 



(continued) 



Marijuana Smoke Condensate 

Table 1 (continued) 



75 



Class of compounds Amount 


Ref. 


Present in tobacco smoke? 


Ethyl- or dimethylpyrazole or 


? in 


Vat- 

i es 


imidazole (5 isomers) 






Benzoxazole 


If) 
1 u 


Mn 


\ Ar*p»t\7l rw/vi (imp 
J -/1LC I V 1 U y 1 1L1111C 


If) 


Yps 
1 c» 


X/lAtrnnQminn tw 
IVlCllly IdllllllU- Ul 


If) 


1 c» 


QTVunniTiAtniM m/nninp 11 S ica m pre 1 
dllllilUlllClliy ipyllLllllC I 1 J loUlllCia^ 






IpyllLllllC Willi 11VC Ul 111U1C Lai UUllO 


If) 




in side chains including one 






uouuie Doiiu, or loniiiiig one ring 






I A1 1 LV\ T~t~l P 1* C \ 

y'-r 1 laUlllClo^ 






Methylfurfurylpyrrolidine (?) 


in 
1 U 


Vac 

i es 


z-.r ropiony lpyriLiine 


If) 




L r- /AceiyipyriLiine 


If) 


"Mn 


Tii tYiptnAfl / "\ i* t>t ri^ /l opptin nwri nitip 

lyillicilly l - Ul CLllyld-CClyipyilLllllc 


inn 

1\J,1 J 


Yps 
1 c» 


^Zi lOUlllCloy 






2-Aminopyridine 


in 
1 u 


i es 


A 1 L r \/1 fw/VQ vr^l p nr iminQ7nlp u/itri 
r\ll^.yipyid.Z,UlC Ui - 11111 LI clZUlC Willi 


? If) 


"Mn 


11VC Ui 111U1C Cd.1 UU11 aLUlllo 111 






oQfiifQtf^ri gimp pnnitil c I (AD i enmprs i 

Od.lUid.LCLl OlUC Ivlld-lll^O^ ISUIIICIS^ 






Methylamino- or amino 


If) 
1 u 


Mn 


niciiiy ip y i dzinc ui -p yiiiiiiLiiiic 






r\t m tat q m i n / a v~\ \ ! t" i ninp 

ui LiiiiicLiiyid.iiiiiiuuyiiu.iiic 






(4 isomers) 






Aminoethyl-, ethylamino-, 


1 u 


Vpc 

i es 


aminodimethyl amino-, or 






tn p t n\fl om i nAmptn\/l t\\71*i ninp 
lllClliy lallllllUlllCLlly ip yllLllllC 






lis 1 L 1 /"\ fYl PTC 1 

\±J IsUlllClo^ 






lji vinyipyriLiiiie, 


If) 
1 u 


Vpc 

i es 


n v rl 1 n\/TiT*r\Ti 'i n n t n n 1 1 np r\r 

dZjd.Lllll V LilUlld-UllLlldllllC Ul 






methyl azaindine (2 isomers) 






111 nn t \ 1 1 n p 
V^lllllUllllC 


3 Jf) 1 1 


"Mn 


M IPAtltlP 

1N1L-UL111C 


3 Jf) 1 1 

J , 1\J, 1 J 


Yps 


J-Vld.Zjd.lld.UllLlldlCllC iz, louiiicio^ 


10 
i \j 


Yps 


\flptnfivi'Qiniiinn\7riHiiip i ?i 
IVICLIIUaV allllllUpyilLllllC ^ :^ 


If) 


Nn 


Tcnniiinnlmp 
loUU U111U1111C 


If) 1 1 


"Mn 


Indazole or pyrrolopyridine 


10 


Yes 


(3 isomers) 






Aminoethyl-, ethylamino-, 


10 


Yes 


aminodimethyl dimethylamino-, 






methylaminomethylpyrazine or 






pyrimidine or 






methyldiaminopyridine (5 isomers) 






8 -Methylquinoline 


10 


No 



(continued) 



76 



ElSohly and ElSohly 



Table 1 (continued) 



Class of compounds 



Amount 



Ref. Present in tobacco smoke? 



2-Methylquinoline 
7-Methylquinoline 
4-Methylquinoline 
Other methylquinolines and 

-isoquinolines (10 isomers, 

14 in all) 
Methylindazole, -benzimidazole, 

or -pyrrolopyridine (12 isomers) 
Pyridine with five or more carbon 

atoms in side chains including 

two double bonds or containing 

one ring and one double bond 

(11 isomers) 
2-tert-Butylphenol 
2 ,4-Dimethylquinoline 
Other dimethyl- or ethylquinolines 

or -isoquinolines (19 isomers, 

20 in all) 

Methyldiazanaphthalene (3 isomers) 
Dimethyl- or ethylindazole, 

benzimidazole, or pyrrolopyridine 

(23 isomers) 
Aminopyrazine or -pyrimidine with 

three carbon atoms in saturated 

side chain(s) or a dimethyl- or 

ethyldiaminopyridine 
Vinylquinoline or phenylpyridine 

(3 isomers) 
Methylvinylquinoline or 

methylphenylpyridine (6 isomers) 
2-Pyridine carboxamide 
Aminopyridine with four carbon 

atoms in saturated side chain(s) 

(3 isomers) 
Azaindanone (?) 
Methylpyridine carboxamide 
Methylpyrrolopyrimidine or 

-pyrazine (?) (2 isomers) 
Dimethyl- or 

ethylpyrrolopyrimidine or 

-pyrazine (?) 
Propyl-, methyl ethyl-, 

trimethylquinoline or 

-isoquinoline (4 isomers) 



10 
10 
10 
10 



3,10 
10,13 



10 
10 
10 



10 
3,10 



10 

10 

10 

10,13 
10 



10 
10,13 
10 

10 



10 



No 
No 
No 
Yes 



Yes 
Yes 



No 
No 
Yes 



Yes 
Yes 



Yes 

Yes 

Yes 

Yes 
No 



No 
No 
No 

No 



Yes 



(continued) 



Marijuana Smoke Condensate 

Table 1 (continued) 



77 



Class of compounds Amount 


Ref. 


Present in tobacco smoke? 


lliiinolinf* cm" icnnmnnlinp \xntn 
V^UlllVJllllC Wl loUU UH1U11I1C WILll 


1 u 


Nn 


1UU1 Ul 111LHC CalUUll dLUlllo 111 






saturated side chain(s) 






(2 compounds) 






iviciii y id.Zja.iid.LJiiLiid.iciic y/ latJiiicia^ 


1 1 
i ~) 




Methylazaindole (6 isomers) 


1 J 


i es 


I A 7Q n on ri t nci 1 f» n (O icnmpvc 1 
v^7 rtZ,dlldHJllLlldlCllC ^" laUlllCio^ 


1 J 




A vunitiritnolpnp ( / icnmpvc 1 
- rtZ,dlldHJllLlldlCllC yZ, laUlllci?)^ 


1 J 


Nn 

IN U 


r\ll d.liyiL[LllI1011Ilc yl) 


1 j 


Nn 
1NO 


An Q7iinnr>lp 
r\Ll d.Z,d.lllUUlc 


1 ? 
1 J 


Nn 


I A v ' 1 1 t~i / 1 f "a 1 I O i c/"\m £»i"c l 
v^7 rtzLdlllUUlC I? latJlllClsJ 


1 1 
1 J 


1 Ca 


\/itnnQ7Qri'innmQlpnp ft icAtnprc 1 
VlliyidZ.dlldUllllld.lCHC ^z, laDlllcis^ 


1 ? 
1 J 


1 ca 


A 7Qinnnlp f ^ icaiyipvc I 
rtzLdlllUUlC latJlllClSj 


1 1 
i J 


Nn 

IN U 


Alkyldiazole (6 isomers) 


1 j 


InO 


iV-Methylazacarbazole 


1 j 


i es 


A hexenylazaindole (?) 


1 j 


INO 


A C 6 diazanaphthalene (?) 




INO 


r\ Ullllclliy IdZdCdLDdZOie 


7 ? 
1 j 


Nn 
INO 


/\I1 clliyidZdCdlDdZOlC 


7 ? 
J D 


Nn 
INO 


ivicLiiyidZaLarudzoie [ft lsuniers ) 


7 ? 
1 j 


I CS 


dZaLaLDdZOie lSUIIieiS ) 


7 1 
1 J 


Nn 
INO 


A 7npo i* r\ ' i "7 f a 1 a / 1 *n t> i" c l 
/\Z,dCdl UdZAJlC \ jL IStJlllClS^ 


1 ? 
1 J 


1 cs 


r\ v^ 4 dZdLalDdZOie 


7 1 
J J 


Nn 
INO 


A C 2 diazole 


J j 


Vac 

i es 


P\ft , irlinp (*k icnmprc l 
ryllUlllC \ J 1&U111C1 


1 1 
i J 


Nn 

IN O 


v^4 ryriuiiie yj lsonieis^ 


7 1 
1 J 


Yps 

i es 


x^yriLiiiic yj isonieisj 


7 1 
J J 


Nn 
INO 


^2 v lnyipynuinc yv isomers j 


7 1 
J J 


Nn 
INO 


A fflh; 1 t\\71*i /H i n 
/\CCly lUyllLllllC 


1 ? 
1 J 


Nn 

IN O 


\/iTnH'n\rt , irlinp is 1 c /~im pre \ 
V lliy ipV 11Q111C ^J) laUlllCiS^ 


1 1 
1 J 


Nn 

IN O 


C 4 Azainaoie 


1 j 


Vac 

i es 


Myosniine'' 


J j 


Vac 

i es 


15 1 r\i;i"i *H \r1 <^ icAmprc\ 
DlUyllLlyl \J 1&U111C1 


1 1 
1 J 


Yps 
1 Ca 


uipynuyi ^^h- lsonicrs^ 


7 ? 


Yps 

i es 


f~* V\i n\rvi /H 

v^^ uiuyiiuyi 


l j 


Yps 
1 Ca 


A 1 -iiUi ■ 1 U , , ,.,-1 1 1 jlc/ 

ivietny 1 Dipyraiy r 


1 j 


Vac 

i es 


i V IVlCLlly lalldLaUlllC 


/ ^ 


Yps 
1 Ca 


Nicotine'' 


7i 


Yes 


Anatabine'' 


7i 


Yes 


Methylbipyridyl'' (3 isomers) 


13 


Yes 


A r -Furfurylnornicotine rf 


13 


Yes 


A r -Furfurylanabasine rf 


13 


Yes 


Cotinine'' 


13 


Yes 


Aminoquinoline rf 


13 


Yes 


A r -Formylnornicotine'' 


13 


Yes 



(continued) 



78 



ElSohly and ElSohly 

Table 1 (continued) 



Class of compounds Amount 


Ref. 


Present in tobacco smoke? 


A/_ A ppfvl an atnVvinp^ 

j V .ri^CLy lallaLaUlllC ^ :^ 


i j 


1 Ca 


Af T<r\t , TYi\flQnQt'aKinA^ / "7^ 
iV -TUllliy ld.Ild.Ld.Ul 11C ^ i^J 


/ ^ 


Yps 


"NAfstlrwl "M\7T"i f \ {~\\t] rwrrm] i r\ i n /' ( ?^ 

iviciiiy ipy nuuy i py iiuiiuinc i 






Af I - It \ / 1 *i /■ m" i / * / a t" i m a » / "7^ 
iv _ _ClliyilHJllllL.ULlllC V, : ^ 


/ ^ 
i j 


Yps 


Af \/Tf»tn\7l an aV\a ci n*=» £ ^ ^ *)\ 
iV-lVlcLliyidilaDaSlllC ^ : ) 


i j 


I CS 


I\/T /"> \ ; 1 n i r»rvli n f''?\ 
IVlCLliy llllCUllllC ^ : ^ 


/ ^ 


Vpo 


A^-Propylnornicotine^ or 


/ ? 
y j 


i es 


Af wl anaMacin 
1 V CLlly IdlldUdSlllC 






A h l/'M'i'A f^ 1 rli a van ar*MtM al £»ne»^ Z''?^ 
r\ ClllUlO-l^-2 U-ld.Ad.lld.UllLlld.lCHC ^ . J 




1 


A mpt M\7l T\\7i*i r\ \t] m <3 I'm a/1 f\t a v /" \ 1 ( r f\ 
r\ lllCLlly lUy llLly llllCLlly !Uld.Z,UlC ^ : } 


/ ^ 
i j 


Yps 


A f -1 r\\TV\ f\ \f1 r\~\(±t m\?1 f\ i a veil c±d 

r\ uyiiuyiiiicLiiy iuid./jUic \-) 


1 ? 
i j 


Yps 


r\ UyilUyl-V^.^ Uld-ZUlC \-J 


J ? 
i j 


Yps 


iv ivicLiiy i _ j-py iiuiiic 




Yps 


r'Qi'liAVQmirlp^ /' ( ?^ 
L.d.1 UUAd.llllUC ^ : ^ 






Prnm /"\n a m iHp 
r 1 UUlUlld-llllUC 


j 




R 1 1 ti rrv^ a m irlf* 
H> ULy 1 UdllllUC 


2 




i^yciopciiLduieiic 


? 




Dimethyltrisulfide 


J 




J , J -UlIIlc Lliy lUAc Ld.Sc 


J 




j, J -i-'llllc Lliy ICy LlODULallcCal DOIllLlllC 


3 
J 




ivicLiiy icLiiyipyrruic 


J 




Til rnptruM tMtiArQ7inp 
UllllCLliy 1U1UC1 dZ,lllC 


2 
J 




iV-ivicLiiyi-z-pyriuiiid.iiiiiic 


J 




111 m£»t rr\/l ft ri \ 7l 11 \ ' vr/ \ 1 p 

L-ziiiicLiiy icuiy ipy noic 


2 
J 




\/ al/^fatniHp 
V dlCl d.llllU.C 


2 
J 




z, ivicLiiuAy j ivicLiiy iuy i ti/jiiic 


-? 
J 




|ji mf>f n\/1 pin ana m i n p i m i H a vol p 

-L/llllCLll y lCLlld.lldllllllC lllllQd.ZjVJlC 


-? 




Trnnnl otip 
i lupuiuiic 


-? 
J 




N|i trnni r*r\1 nip 

1> 111 VJJJl^UllllC 


-? 
J 




v^-y-/\ii^y id.iiniic 






1^ A llri7m'\;T'"7nlp 

v^^-rtii^y ipy i d.z,uic 


J,JO 




111 rnptn^n otn \ /l f\\7vi in iiiniifl 

-L/iincLiiy icLiiy ipy iiiinuuiic 


J 




ivicLiiyi d.ccLyi pyiiuic 


2 
J 




1 /d. KPn7r>nninnnp 
1 ,t- _ DC11ZjUUL1111U11C 


2 




A 1 a m iHp 

rtijvy idiinuc 


2 




in A mmnnriPiiAl 
AA£ _ rtllllllUpilCllUl 


2 
J 




1 Riitrw^f / nrAn'i n 1 
1 D UHJAy-Z, _ piUUd.llUl 


2 
J 




Methylpropionylfuran 






3-Methyl-5-triazolo(4,3-a)pyrazine 


3 




A^-(a-picolidene)-n-propylamine 


3 




5 -Hy droxyindole 


3 




C 8 -Alkylamine 


3 




Dimethyltetrazine 


3 




C 4 -Alkylpyrazole isomer 


3,18 




C 9 -Alkylamine 


3 





(continued) 



Marijuana Smoke Condensate 



79 



Table 1 (continued) 



Class of compounds 



Amount 



Ref. Present in tobacco smoke? 



C 5 -Alkylpyrazole isomer 

3 -Methyl-4-ethylpyrrole 

C 9 H 12 

C 9 H 14 

C 10 H 14 O 

C 8 H 12 

Phenoxyethanol 

Aminobenzamide 

Phenylurea 

Methylthiopyridine 

Methylquinoline 

C 6 -Alkylpyrazole 

Methoxybenzaldehyde 

4-Methyl carbostyril 

C 4 -Alkyl pyrazine 

Propylmethoxyphenol isomer 

3 -Methyl- 1 , 8 -naphthy ridine isomer 

Pyridine carboxylic acid, methyl 

Benzoic acid, 3-methyl 

Phenyl pyrazoline 

3,4-Dimethylbenzoic acid 

Benzylacetate 

1 ,2-Dihydro-3-isobutyl- 

1 -methylpyrazin-2-one 
Ethyl hydroxyacetophenone 
2 ,4-Dimethylquinazoline 
Phenyl methyl urea 
Phenyl pyridine 
Propylbenzimidazole 
Aminoquinoline or C 9 H 8 N 2 
Dimethylnaphthyridine 
Af-Phenylacrylamide 
Methoxypropylpyrazine 
Phenyl alcohol 
Ethoxybenzaldehyde 
Tolyl azide 

Phenylmethylguanidine 

C 6 -Alkylphenol 

C 3 -Alkylbenzimidazole 

1-Decanol 

C 5 -Alkylpyrazine 

Alkylamide 

Dimethyl benzimidazone isomer 
Trimethyl-2-oxo-l,2,3,4- 
tetrahydropyrimidine 



3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 

3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 



(continued) 



80 



ElSohly and ElSohly 



Table 1 (continued) 



Class of compounds 



Amount 



Ref. Present in tobacco smoke? 



Dimethoxybenzene isomer 

Aminodimethylpyrimidine 

Hydroxymethylquinoline 

Methylbenzoxazole 

ferf-Butyl-hydroxybenzoate 

C 1() H 12 0, (ester) 

Methyl-w(pyrid-2-yl)dihydropyrrole 
C 12 H 18 

Methylaminonaphthyridine 
Diphenylamine 

C 9 H 10 O 3 

Ethoxyquinazoline or isomer 
Diethylphenylene diamine 
C5H5N, isomer 
A^-Dimethyl-AT~(p- 

methoxyphenyl)formamide 
Nitroacetamide 
2,2 ,4-Trimethy lpenta- 1 , 3 -diol 

di-isobutyrate 
C u H 6 (alcohol) 
A?,F-Dimethyl-A f ,F-diethyl-p- 

phenylene diamine 
Dimethylbenzimidazole 
Diethyl biphenyl 
A r -Benzyl-4-aminobutyronitrile 
Af-Methyl diphenylamine 

1- Undecanol 

Dimethylnaphthyridine or C 10 H 10 N 2 
isomer 

Trimethylnaphthyridine or C n H 12 N 2 

isomer 
Alkylamide 

Hexanenitrile 3(pyrrolidinylmethylene) 

or (C n H lg N 2 ) isomers 
Aminodiphenylene oxide 
Methylpteridinone isomer 
Alkyl nitrile 

2- (Propylamino)benzothiazole 
C 13 H 22 N, isomer 
Phenylbenzothiazole 
Aminomethylquinoline 
Tetramethylcyclopentanedione 
1 -Methyl-dihydro-P-carboline 
Alkylamine 
Alkylthiopyridine 



3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 

3 
3 

3 
3 

3 
3 
3 
3 
3 
3 



3 
3 

3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 



(continued) 



Marijuana Smoke Condensate 

Table 1 (continued) 



81 



Class of compounds Amount Ref. Present in tobacco smoke? 



Lystrin 


3 


MA^-Dicyano-4-methylphenylene 


3 


diamine 




Alkyl thiopyridine 


3 


7,8-Benzoquinoline 


3 


5,5-Diphenylimidazolid-4-one 


3 


1 -Methylphenazine 


3 


w-Dodecanol 


J 


Alkyl amide 


3 


Alkyl amine 


3 


Methyl palmitate 


3 


Dimethylnaphtho (2,3,6-) thiophene 


3 


Homologous aliphatic alcohol 


3 


(w-tridecanol) 




1 -Methyl-(3-carboline 


3 


n-C 28 H 5g (octacosane) 


3 


n-C 29 H 60 (nonacosane 


3 


Alkyl phthalate 


3 


m-C 30 H 62 


3 


(3-carboline 


3 


p-Cumylphenol 


3 


Dibutylphthalate 


3 


Benzyl acetophenone 


3 


M-Tetradecanol 


3 


Diphenylpyridine isomer 


3 


Alkyl ester 


3 


Dihydroxymethyl phenyl quinazoline 


3 


Ditolylethane 


3 


1 - Azido naphthalene 


3 


1 -Phenyl decane 


3 


Dimethyl-P-carboline isomer 


3 


Alkylamide 


3 


Phenylbenzimidazole 


3 


2,6-Diterbutylnaphthalene or isomer 


3 


C 14 H 8 3 isomer 


3 


Methylthiazolopyrimidine 


3 


8-Acetoxy-pyrazolobenzo-as triazine 


3 


orC„H 8 N 2 4 




Methyl stearate 


3 


Methyl phenylcinnoline or C 15 H 12 N 2 


3 


isomer 




2-Thiocyanatodiphenylamine 


3 


Methylpyriloindole 


3 


Alcohol (n-pentadecanol ?) 


3 


Naphtho- sy dinone 


3 



(continued) 



82 



ElSohly and ElSohly 



Table 1 (continued) 



Class of compounds 



Amount 



Ref. Present in tobacco smoke? 



n-Hexadecanol 
n-C 22 H 46 (Docosane) 
Alkylamine 
C 12 H 10 N,O 4 isomer 
n-C 23 H 4g , tricosane 
Homologous aliphatic alcohol 

(w-heptadecanol ?) 
«-C 24 H 50 (Tetrosane) 
DL-Cannabichrome 
«-C 25 H 52 (Pentacosane) 
3-ra-Pentyl-delta-9- 

tetrahydrocannabinol 
Dioctyl phthalate 
«-C 26 H 54 (Hexacosane) 
3-M-Pentyl cannabinol 
«-C 27 H 56 (Heptacosane) 
Alkylamide 
«-C 2S H 5S (Octacosane) 
Saturated hydrocarbon 
n-C 29 H 60 (Nonacosane) 
Alkylphthalate 
Saturated hydrocarbons 
m-C 30 H 62 
Acidic 

Hexanoic acid 
Heptanoic acid 
Octanoic acid 
Benzoic acid 
Salicylic acid 
Hexadecanoic acid 
Heptadecanoic acid 
Octadecanoic acid 
Phenylacetic acid 
(3-Phenylpropionic acid 
p-Hydroxybenzaldehyde 
Vanillin 

2-Hydroxy-3-methyl-2- 

cyclopenten- 1 -one 
Myristic acid 
Palmitic acid 
Stearic acid 
Linolenic acid 
Furoic acid 
Nonanoic acid 
Decanoic acid 



6% 

9% 

13% 

23%, 

5% 

0.2% 

0.3% 

0.2% 



9.3% 



4.6% 

35.2% 

10.8% 

4.9% 

3.1% 



3 
3 
3 
3 
3 
3 

3 
3 
3 
3 

3 
3 
3 
3 
3 
3 
3 
3 
3 
3 
3 

7,14,15 
7,14 
7,14 
7,14,15 

7 

7 

7 

7 
8,15 

8 

8 

8 

8 

14 
14,15 
14,15 
14,15 
14,15,18° 

15 

15 



(continued) 



Marijuana Smoke Condensate 



83 



Table 1 (continued) 



Class of compounds 



Amount 



Ref. Present in tobacco smoke? 



Glutaric acid 
Dodecanoic acid 
Phenylisopropionic acid 
Tetradecanoic acid 
Palmitoleic acid 
Palmitolenic acid 
Oleic acid 
Lenoleic acid 
Arachidic acid 
Eicosanoic acid 
Eicosadienoic acid 
Behenic acid 
Erucic acid 
Tricosanoic acid 
2-Ethyl-3-hydroxy-5- 
pentylbenzoic acid 
Lignoceric acid 
Tetracosatetraenoic acid 
Hexacosanoic acid 
Hexacosadienoic acid 
Octacosanoic acid 

2- Methyl butanoic acid 

3 - Methyl butanoic acid 

4- Pentenoic acid 
Phenolic 

Phenol 

Cresols 

Guaicol 

Catechol 

Hydroquinone 

p-Hydroxyacetophenone 

a-Dimethylphenol 

(3-Naphthol 

4-Methylguaicol 

o-Cresol 

/>Cresol 

p-Ethylphenol 

p-Vinylphenol 

Catechol 

m-Cresol 

o,p-Divinyl phenol 

o-Isopropenylphenol 

4-Hy droxy- 3 -methoxy styrene 

m-Hydroxy-p-methoxystyrene 



0.6%, 7.6% 

1.2% 
0.5% 
3.1% 
0.6% 

3.7%, 2.6% 



9.2% 
1.9% 
2.1% 
12.1% 



75 
75 
75 
75 
75 
75 
75 
75 
75 
75 
75 
75 
75 
75 
75 

75 
75 
75 
75 
75 
75 
75 
75 

3,7,14, 
15,18" 

7 

7 

7 

7 
7,14 
3,8,18" 

8 

8 

14,15,18" 
14,15,18" 
14,18" 
14,18" 
14,15,18 

15 

15 

15 

14 

15 



(continued) 



84 



ElSohly and ElSohly 

Table 1 (continued) 



Class of compounds Amount 


Ref. 


Present in tobacco smoke? 


/ ZL 111 n\mrAvifonicnlp 
Z,,T" _ _L'lliy UIUAy dllloUlt 


i j 




p-Hydroxybenzaldehyde 


Q 
O 




o-ny uruxy DeiizaiLieiiy ue 


7 ^ 

J J 




/i.T-IvnrnYUiifptn'n npn ntip 
U XIV Ul VJAy d.CCUJUllCllL7llC 






\_/ll V CIU1 


iJ,JO 




j-isopropy i-j-ny uruxy Deiizdiueiiyue 


7 ^ 




2, 4-Dihydroxybenz aldehyde 


1 c 
7 J 




p-Hydroxybenzyl-2-butenyl ketone 


7 C 
7 J 
















D CllZdlUCliy Lit 


^ in 




A f* n 4"/Vn n OT1 /"All O 

rttC lUpiltllUllC 


2 
o 




.T 1 UpiUpiltllUllt 


o 




B enzonitrile 


2 
O 




i uiuiiiLriie 


e 
o 




Benzylcyanide 


Q 
O 




P -T llClly ICllly 1L/V tllllUC 


s> 
o 




' I r~\ ci nimfitn\/l at f»tri\7l mnr»lpc 
lllltt LllllltLliyi Ul CLllyl lULlUlta 


^ JO 




KJllC llllllClliyi-lllCLliy IClliyi - Ul 


o, ziy 




Ul UUy 1111L1U1C 






' 1 \~\ a me*tr\\rl PQrr\Q7Alpc 
1111CC llltlliyi L,dl UdZ,UlC» 


o, ziy 




I lnp r\ i m e»rri \/l i~\r c±t n\J 1 PQfnQ 'vrtlc* 
KJllC LlllllClliyi Ul CLliy IL-dl UdZUlt 


o, ziy 




P 1 1 fl 1 1 1* Q 1 

.T Uil Ul dl 


s> 
o 




J -IVie Lily 11 UT1 Uldl 


Q 

o 




2-Acetylfuran 


e 
o 




S -A/Tpt n\/1 - /— nr , f i t\'1 Til to n 
J iviciliy 1 dl^Ciy 11 Ul dll 


o 




4-Hydroxy-6-/i-pentylbenzofuran 


e 
o 




S - T-I vHrnw. / - rT-r\i 2 *nf"\/1 - / 1— T-tn pt n vl - 
J nyuiUAy / ilt UCllLyl All lllCUlyl 


o 




6-/2-Pentylbenzofuran 






/ v - 111 tn pt n\/1 - i —\\\jc\vr\~Y~\j—l — vi— 
z,,z, inline- Lily i j ii y LiiUAy i -ti 


S 
o 




peniy iLiirunieiie 






V^dlllldUll Ul dll 


O, Z17 




j 1 Ivn A 3(4) tptrornjnmr'QnnQninAl 

z,-\jA\j-L\ -LeLidiiy Lirocdiiiiauiiiui 


o, Zf 




Cannabichromanone 


o to 




ZA - 1 CLlaliy LirOCdllllaDlIlUl IIlcLIiyi 


c 
o 




ether 






Dehydrocannabifuran 


S,20 




Cannabinol methyl ether 


S 




Ethyl methyl benzene (2 isomers) 


7S 


Yes 


C 2 -Ethylbenzene 


7S 


No 


Limonene 


78 


Yes 


C 2 -Styrene 


78 


Yes 


Undecene 


78 


Yes 


Undecane 


78 


Yes 



(continued) 



Marijuana Smoke Condensate 

Table 1 (continued) 



85 



Class of compounds Amount 


Ref. 


Present in tobacco smoke? 


1\ A at t 1 1 n r\ pn p r\r ni nurlrn 
IVlCllly 1111UC11C Ul UlllyU.lU _ 


1 R 


Yet 


n n nn t"n Qlpnp | 7 1 com pre ) 
lld|Jllllld.lCllC l^Z, laUlllCI a J 






M ann t n qIptip 
1> d.UllLlldlCllC 


1 R 
1 o 


ly U 


Dodecane 


1 2 

lo 


Vat- 

i es 


An i iva ty~\ p i" /"\t trinp^Qnp 
rtll 1»L/111C1 Ul LIlU.COd.llC 


1 R 


"Mn 


2-Methylnaphthalene 


1 o 


Vat. 

i es 


1 -Methylnaphthalene 


1 o 


i es 


A n pmi/monn triQlpnp 
r\ll CLlly llld.Ullllld.lCHC 


1 o 


IN u 


An ethyl naphthalene 


7 O 


Mn 


A GPGnm ti A rnp n p 

r\ &C&U LllLCl IJC11C 


1R 

1 o 


Nn 


A tpfr^iripppTip 

LCL1 d.UCCCHC 


1 R 
1 o 




(a-I^ tirvrxnri \il 1 ptip 
p L-di yuuiiy iiciic 


7# 


Nn 

IN (J 


RpririmntPTip 
IX -Del gdlllULCllC 


7 O 


"Mn 

IN U 


Humulene 


7 £ 
1 O 


InO 


A sesquiterpene 


7 Q 


InO 


K-FarnPGPtip 

y) J. dlllCACHC 


18 


Yes 


A cpcnm fprnpn p 
SCaUUlLCI IJC11C 


1R 
1 o 


Nn 

IN (J 


A GPGnm fprnpn p 

&C&U U.1LCI IJC11C 


1 R 
1 o 


Nn 

IN (J 


A cpcniii fprnpii p 
r\. staU UlLCi IJC11C 


1 R 
1 o 


Nn 

IN (J 


A c p c n 1 1 1 fpmpn p 
r\ &C&UU1LC1 UC11C 


7 O 


Nn 

IN U 


Bisabolene 


7 t? 
7 O 


InO 


Ppti ta f\ pp a n p 

r CllLd.LlCCd.llC 


1 R 
1 o 




A naphthalene 


7 p 
i o 


INO 


A sesquiterpene 


7 Q 
J o 


INO 


A dehydrosesquiterpene 


7 Q 
1 o 


INO 


A sesquiterpene alcohol 


7 Q 
7 O 


INO 


iNtJi piiy LC11C 


1R 
1 o 


Yps 


A n nr'tiMPPPnp 
r\ll UC Ld.UCCCllC 


1R 
l o 


Nn 

IN O 


in eopiiy Lauieiie 


i o 


i es 


A nonadecene 


7 
i o 


Vac 

i es 


A n Pip^cQniPHP 
r\ll CICUSdUlCllC 


1R 
l o 


1 


A n Pip^cQniPHP 
r\ll CICUSdUlCllC 


1R 
l o 


Nn 

IN O 


Cannabicitran 


7 Q 
i o 


INO 


Tetrahydrocannabidivarol 


7 Q 
J o 


InO 


1&ULCL1 all y lOCallllaUlllOl 


j o 


Nn 

IN O 


v^allllaUlQlOl 111U1HJ111C111 y 1CL11CI 


7, 9 
j o 


Nn 

IN O 


Cannabichromene 


7 Q 
i O 


INO 


monomethylether 






Cannabicyclol 


7S 


No 


Cannabidiol 


78 


No 


Cannabichromene 


75 


No 


A 9 -Tetrahydrocannabinol 


18 


No 


A dihydrocannabinol 


18 


No 


Cannabinol 


18 


No 


Heptacosane 


18 


Yes 



(continued) 



86 




ElSohly and ElSohly 


Tabl 


e 1 (continued) 




Class of compounds 


Amount Ref. 


Present in tobacco smoke? 


Octacosane 


18 


Yes 


Nonacosane 


18 


Yes 


An isomer of triacontane 


18 


Yes 


Triacontane 


18 


Yes 


Myrcene'' 


18 




An acyclic diene'' 


18 




Decane rf 


18 




A dihydrolimonene'' 


18 




A C 4 -benzene 


18 




Tridecene rf (2 isomers) 


18 




Nocotine'' 


18 




Solanone rf 


18 




A tetradecene'' 


18 




A dihydrosesquiterpene'' 


18 




An isomer of pentadecane rf 


18 




A hexadacene'' 


18 




Eicosatetraene'' (2 isomers) 


18 




Androstadienone rf (2 isomers) 


18 




An eicosadiene rf 


18 




Eicosatriene d (2 isomers) 


18 




Dihydrosesquiterpene rf (2 isomers) 


18 




Pentacosane'' 


18 




Squalene'' 


18 




An isomer of squalene'' 


18 




An isomer of nonacosane rf 


18 




An isomer of hentriacontane d 


18 




Hentriacontane'' 


18 




(B) Polar neutal 






2-Methylphenol (2 isomers) 


18 




Dimethylphenol (3 isomers) 


18 




C 3 -Phenol (2 isomers) 


18 




Methoxymethylphenol'' 


18 




Hydroxyfuroic acid (2 isomers) 


18 




Methylbenzenediol (2 isomers) 


18 




A vinylmethoxyphenol 


18 




(e.g., isoeugenol) 






C 2 -Benzenediol (5 isomers) 


18 




A methylhydroxyfuroic acid 


18 




A methyl indole 


18 




A hydroxyacenaphthalene 


18 




A styrenediol (2 isomers) 


18 




A pentenylphenol 


18 




A C 4 Methoxyphenol 


18 




A methylstyrene diol 


18 




A methoxymethylbenzenediol 


18 




A dichlorobenzenediol'' 


18 





(continued) 



Marijuana Smoke Condensate 

Table 1 (continued) 



87 



Class of compounds Amount Ref. Present in tobacco smoke? 

A styrenetriol 18 
A me thoxy naphthoic 18 
A methoxydihydroxybenzofuran 18 
(C) Polynuclear aromatic 



hydrocarbons 



Methylindole 


6.3' 


16 


0.3' 


Ethylindole 


3.2' 


16 


No 


Dibenzofuran 


1.0 P 


16 


No 


Methylacenaphthalene 


1.4' 


16 


0.5' 


2-Methylfluorene 


0.8' 


16 


0.3' 


1 -Methylfluorene 


1.4' 


16 


0.3' 


Phenanthrene 


8.9' 


16 


8.5' 


Anthracene 


3.3' 


16 


2.3' 


EthylmethylbiphenyF 


0.4' 


16 


0.1' 


Methylcarbazole 


3.4' 


16 


No 


3 -Methylphenanthrene 


2.6' 


16 


2.0' 


2-Methylphenanthrene 


5.3' 


16 


5.6' 


2-Methylanthracene 


3.2' 


16 


2.4' 


4//-Cyclopenta[c/ ef\ 


3.2' 


16 


2.4' 


phenanthrene 








9-Methylphenanthrene 


2.9' 


16 


2.7' 


1 -Methylphenanthrene 


4.2' 


16 


3.2' 


Methylcarbazole 


3.6' 


16 


No 


Methylcarbazole 


5.1' 


16 


No 


Methyl-4Z/-cyclopenta[flf ef\ 


3.1' 


16 


1.6' 


phenanthrene 








Methylcarbazole 


3.0' 


16 


No 


Ethylphenanthrene or 


0.3' 


16 


0.4' 


ethylanthracene 8 








Ethylphenanthrene or 


0.7' 


16 


0.6' 


ethylanthracene 8 








Ethylphenanthrene or 


0.6' 


16 


0.5' 


ethylanthracene 8 








Ethylphenanthrene or 


0.7' 


16 


0.5' 


ethylanthracene 8 








Ethylphenanthrene or 


1.5' 


16 


0.8' 


ethylanthracene 8 








Ethylphenanthrene or 


0.7' 


16 


0.6' 


ethylanthracene 8 








Ethylphenanthrene or 


0.6' 


16 


0.7' 


ethylanthracene 8 








Ethylphenanthrene or 


3.0' 


16 


1.6' 


ethylanthracene 8 








Ethylphenanthrene or 


4.3' 


16 


1.8' 



ethylanthracene 8 



(continued) 



88 



ElSohly and ElSohly 

Table 1 (continued) 



Class of compounds 


Amount 


Ref. 


Present in tobacco smoke? 


htnvlnripn arthrpfip c\r 

LZiliiy lUUClldllLlll C11C Ui 




1 u 


1 Q e 
1 .y 


exf r\\Tl cintnfci r'cxn exS 
C Lll V ld.ll 111! dCCllC^ 








nuui diiuiciic 


rl Q e 

o.y 


1 u 


O.J 


P t ri \rl i"\ri <=>n q n t ri t*£»n ni* 
L/lllylUllClldllLlllCllC Ul 


u.u 


1 u 


1 f," 
1 .u 


rl\/~ l QntnrQ Aptia 
C Lll V ld.ll 111! dCCllC 








R t~i r 7 '\ t ti Qnn t~ ri o 1 «n ex 
OCllZ,d.CClld.Ulllild.lCllC 


9 Qe 

Z,.y 


16 
1 u 


1 0» 


T-7 1 ri \rl i"\ n p> yi q yi t rit"£»n ^ r\r 
XZ/LllylUllClldllLlllCllC Ul 


A Qe 


16 


T. Ae 


exf n \7l ciritnfci fan 
C Lll V ld.ll Llll dVCilC 








P^ffPTlP 

r y 1C11C 


u.u 


16 


u.o 


J3Lllyl _ T- - /7 _ CyClL>|JCllLd.Lct c /J 


1 Q e 


16 


VJ. 1 


UllClld.ll Llll CJLIC° 








T-HTri\/~l A. J-f ^i/plnnpntQ l/i sj t\ 

x_/Liiyi _ T--/j _ cyciuuciiLd.Lct a j\ 


9 9^ 


16 
1 u 


VJ. 1 


v\ ri ex n q n t rii*/^n/^,f 
UllClld.ll Llll CUC° 








i_/Liiyi-^-/7-cyciopciiLdLc/ c /j 


1 V 


16 


1 A' 


11 \~\ ex 11 Q n f hranaC 

UllClld.ll Llll CJ1C° 








i_/Liiyi-H— /7-cy ciupciiLd-Lu t?yj 




16 
1 u 


yj.o 


UllClld.ll Llll CJLIC° 








T-ht ri\/~l nipt ri\rl ti rif^n Qtitnvpn ex cw 

i_/Liiy iiiicLiiy iuiiciid.il liii cue ui 


w.o 


16 
1 u 


W.J 


exf ri\7l mot rT\? 1 Q 11 l"rli*Q cexy-\ fxf 

CLliy llllCLliy 1 d.111111 aCCllC 








Ethylniethylphenanthrene or 


1 Ae 


16 
1 


u. / 


athl 7 \ mat r"l\M Qlltln'OPAflA/ 

cLliyililcLliy 1 d.llLlliaccIlc 








Ethyl-4//-cyclopenta[<^ ef\ 


Ae 


1 


1 £*e 

1.0 


t~\Y\fxy% q n t nrfxncxB 
UllClld.ll Llll CUC° 








1 rT\ 7 1 T 111 AVO Tl f" rl *^*n ex 

lVlcliiyillUOld.il Lllclie 


4.U 


16 


A f\' 


\A extr\ tT ii /irn ntnPTiP 
1V1CL11 V 111UU1 dllLllCllC 


1 el e 


16 
1 u 


1 

1 .0 


IV/T/^lrl 1 fl n 71V) nmPTlP 
1V1CL11 V 111UU1 dllLllCllC 


^ r\ e 
J.O 


16 
1 u 


J.U 


R pii7aI /"l Tl ii *~\tv*n£i 
JDC11Z,ULCJ 11UU1C11C 


A e 


16 
1 u 




/ f>t ri\/~i niffptip on/1 Kp n 1 /i 1 

z, _ ivicLiiy luyiciic aim uciiZjU^t/j 




16 
1 u 


J.J 


tI i i r>fP n o 
11UU1C11C 








T-ht ri\/~ 1 nipt ri\rl r\ r\exr\ Qntrrfpn ex r\r 

i_/Liiy iiiicLiiy iuiiciid.ii liii cue ui 


9 


16 
1 u 




exf r\\7l rx~\exf ni; 1 q n l"rl1*CI Cfxr~\ exf 

CLliy llllCLliy 1 d.111111 aCCllC 








A- \/l ex f n\j\ niffptip 

H- _ ivicLiiy luyiciic 


A \e 
t T. 1 


16 
1 u 


A A' 


1 \/l exf n\7l rwifex-nex 

i -ivicLiiy luyiciic 




16 


J.U 


\/\ ext\*-\ j 1 t| ii i^\t*Q ntrlPTIP 
IVlCLliy 111UU1 d.llLllCllC 


yj.o 


16 
1 u 




\A exf\* -fl ii /\r'i ntnPTIP 
IVlCLliy 111UU1 d.llLllCllC 


w.u 


16 
1 u 


W.J 


T-7 1 n\7l Tl 11 nrQTltn exri ex /"II" 

L/LliyillUUld-lllllCllC Ul 


1 \ e 
i . i 


16 
1 u 


i . J 


ri\rl tufvpnp? 

c Liiy iuy i ciic° 








Ethylfluoranthene or 


0.3' 


16 


0.5" 


ethylpyrene 11 








Ethylfluoranthene or 


0.5' 


16 


0.9" 


ethylpyrene 5 








Ethylfluoranthene or 


1.1« 


16 


1.0" 


ethylpyrene 11 








Ethylfluoranthene or 


2.V 


16 


2.4" 


ethylpyrene s 









(continued) 



Marijuana Smoke Condensate 

Table 1 (continued) 



89 



Class of compounds 


Amount 


Ref. 


Present in tobacco smoke? 


P t n\fl tl nnrQti tri ptip / a i* 
H/LliyillUUlalllllCllC Ul 


9 1 e 
i~. i 


1 o 




£»t \fl YV\rt"*i , M 

C ILly ipy i cue 








P t \rl tl 11 AfQ nth anp /~\-r 
L/LliyillUUldlllllCllC Ul 


L.J 


1 u 


9 He 


f*t ri\rl r\~\jrf*np*R 
C Lll y ipyiciic 








P t \rl tl ii Afa nth £»n f~\r 
I_/LliyillUUldlllllCllC Ul 


i 


1 u 


1 9.' 


C Lily IJJy 1 CilC° 








P 1 ri \7l tl ii ni*QTitn £*n /"\ i" 
L/LliyillUUldlllllCllC Ul 


1 He 
1 . / 


16 


1 f\ e 


£»t r*\rl r\~\7r£*Yt(*R _l_ q r*f»t H m~»i*Qn t ri £»r\£i 
CLlly lUy 1C11C° T O.LC11UU1 dllLllCllC 








P tri\rl tl ii ririnth f~\r 
l_/LliyillUUldlllllCllC Ul 




16 




C Lily lUy 1 C11C° 








P t n \7l tl ii nrontn anp /~\-r 
L/LliyillUUldlllllCllC Ul 


9 V 

Z.J 


16 




cLiiy ipy rone* t acepyrciene 








P t \\ \7l tl ii nrintn /_■» r~\ & cvf 
L/LliyillUUldlllllCllC Ul 


1 9 f 
1 .z, 


16 
1 u 


1 A' 


cLiiyipyrciie* 








Ethylfluoranthene or 


1 

1.0 


1 


1 He 


cLiiyipyrciie* 








P t r\ \/l tl ii ni*Qntn £»n /*\*" 
L/LliyillUUldlllllCllC Ul 


1 A e 

1 .H- 


16 
1 u 


1 .J 


C Lily ipy 1 C11C° 








RahtaI o /? 1 1 tl i i ai'q n t ri f± 
1jC11Z,ULx " tJllLLUld-llLllCllC, 


n A e 


16 
1 u 


n A' 


CLiiy ipyiciic Ul 








f*t r\\7l tl ii f~\rckY\ tri f»n 
CLlly 111 UU1 dllLllCllC 








DCilZ, [if J dllLillaCCllC 


J. J 


16 
1 u 




V^lll y SC11C 


J.J 


16 
1 u 




P t r\ \7l tnptrun tl n n tnp n /"» tw 
L/Llly llllCLliy 111L1U1 dllLllCllC Ul 




16 
1 u 


v.o 


£»t \/l mpt h\7 1 mrfpn f*/ 

CLiiy iiiicLiiy ipy i cut/ 








P t n \7l mpt rrw 1 tl 1 1 r\rct n t n f*nf* tw 
L/Llly llllCLliy 111L1U1 dllLllCllC Ul 


u. / 


16 
1 u 


u.u 


f*t ri\f 1 mpfn\n n\rt" f*/ 
CLlly llllCLliy lUy 1 C11C J 








P t r\ \7l tnpitrun tin n tnp n /"» tw 
L/Llly llllCLliy 111UU1 dllLllCllC Ul 


yj.y 


16 
1 u 




£»t n \7l mAtrun niffpti f*/ 
CLiiy llllCLliy lUy 1 cut? 








P t r\ \7l m ptn "\ / 1 tt n n tnpnp tw 

i_/Liiy iiiicLiiy iiiuui diiLiiciic ui 


1 .w 


16 
1 u 


n i c 


^»t ri\/l mptn\n i~\ \ ' vf* 1 1 e>T 
CLiiy llllCLliy lUy 1 C11C J 








P t r\ \7l m ptn "\ / 1 tt n n t r\ pnp tw 

i_/Liiy iiiicLiiy iiiuui diiLiiciic ui 


w.o 


16 




CLiiy llllCLliy lUy 1 C11C/ 








P t n \7l tnpitrun tin n t h i^ni^» 

C/Liiy iiiicLiiy iiiuui diiLiiciic ui 


1 .w 


16 
1 u 


n i c 


i^»t r1\7l lYipt rl\7 1 1~\ \ ' Vf* 11 f>f 
CLiiy llllCLliy lUy 1 C11C7 








P t n \7l mot ri\7 1 tl n /"M"'i n tnpnfl tw 

i_/Liiy iiiicLiiy iiiuui diiLiiciic ui 


yj. i 


16 
1 u 


u. / 


CLiiy llllCLliy lUy 1 C11C/ 








Methylchrysene or 




16 


0.6" 


methylbenz[a]anthracene 








Methylchrysene or 


1.0' 


16 


0.5" 


methylbenz[«]anthracene 








Methylchrysene or 


2.1' 


16 


2.2" 


methylbenz[a]anthracene 








Methylchrysene or 


2.1' 


16 


2.2" 



methylbenz[a]anthracene 



(continued) 



90 



ElSohly and ElSohly 

Table 1 (continued) 



Class of compounds 


Amount 


Ref. 


Present in tobacco smoke? 


IVitlll y 1L.111 y SC11G UI 


1 O 


1 


1 1 ' 
1 . 1 


IIlcLIiyiDCllZ [t/ JdlllllidLeilc 








\fl*sTri\7l c n r\ i c p n p cw 
IVlCLlly 1L-I11 y SCllC Ui 


yj.y 


1 u 


w. / 


m pf n \7l r\pn 7I /i 1 on mt"QPAHA 
lllCLiiy LUCllZ^^ti J dllllli d^CllC 








IV /| ath Til ^Krt^cpnA iw 
IVlClliy 1L-111 y »C11C Ui 


Z..Z. 


1 u 


1 .y 


IIlcLIiyiDCllZLuJallLlirdLcllc 








1\/T pfn <^ni*^f caup /m' 
IViCLll y 11.111 y scilc Ui 


9 He 


1 u 


9 Qc 


iT-i / 1 1"\ \ / 1 r"\ p n 7I /i 1 on mfQPATiA 

111c Liiy iuciiz, Lti j d-iiiiii decile 








jj liidpii Liiy 1 


U.J 


1 


W.J 


R 1 n qt"\ n t n\f l 
DllldUllLlly 1 


W.J 


16 
1 u 


W.J 


Th t n \rl r» riv\7c pnp r"\T" 

L/Liiyiciii y sciic ui 


yj.o 


16 


w. / 


P t \ / 1 n j^Ti "y I / ; 1 Qtitnfci aatip,? 
C Lll y IUCIIZj Lti J dllllli dcciic- 








Tht n\7l r» riv\7c pup r\r 

L/Liiyiciii y sciic ui 


w.u 


16 
1 u 


w.u 


pt r\\TI nPH7l /ll QtltnfCI z" 1 P T"l P ? 
C Lll y 1 UC11Z Lti J dll 111! dUCllC 








Tht n\7l r» riv\7c pup c\r 

L/Liiyiciii y sciic ui 




16 


w. / 


pt n\?l nPH7l /ll Qlltnl"') ApfiaC 

c lii y iuciiZj Lu j diiiiii a^ciic 








Th t n \fl r» riv\7c pn p a 1" 

L/Liiyiciii y sciic ui 


W.J 


16 
1 u 


w.u 


cLliyiDfcJllZLuJdllLlirdCcIlc* 








i_/Liiyiciiry sciic ur 


1 . j 


16 


n 7« 
w. / 


pt n \7l r\pn "v I / / I intni*ci /"*pn p.? 
C Lliy 1UC11Z Lti J dllllli ctL-CilC 








P t n r» riv\7c pn p cir 

L/iiiyiciii y sciic ui 


w. / 


16 
1 u 


w. / 


pt n\?l Kph7I /il onthfa /"*pn p.? 
c my 1 UCilZ Lti J dll 111! ctL-CilC 








Tht n\7l r» riv\7c pn p cir 

L/iiiyiciii y sciic ui 


A? 

W.T- 


16 


W.J 


pt n\?l r\pn 7 1 n 1 Qtltnfd pannS 

c my luciiz Lti j diiiiii dcciic- 








P t n\7l r* riv\7c pn p cir 

L/iiiyiciii y sciic ui 


w. / 


16 


w. / 


pt n\?l Kph7I /il Qtitnc;! /"*pn a,? 

c my 1 uciiz Lti j dii nil allelic 








Methylbinaphthyl 


U.O 


J 


U.O 


TVIpth^l Kin Qr\h tVi\/1 
IViClll y lUllldUllLiiy 1 


A.' 


16 
1 u 


if 

W.T- 


IViCLll y lUllldUllLiiy 1 


A.' 


16 
1 u 


W.J 


Methylbinaphthyl 


U.O 


J 


U.J 


ivicui y luiiiduiiiiiy i 


W.J 


16 
1 u 


W.J 


Th t r\\7l mAtrn/1 c n f\ j c pn p f~\r 

i_/Liiy iiiicLiiy iciiiy aciic ui 


W.J 


16 
1 V 


w.o 


ethylmethylbenz [a] 








anthracene^ 








Ethylmethylchrysene or 


U.J 


J 


M Ac 
U.4 


ethylmethylbenz [a] 








■itif nt'Qr'pn p/ 
dllllli d^CilC 








Ethylbinaphthyl 8 


0.4' 


16 


0.4" 


Ethylbinaphthyl 8 


0.3« 


16 


0.3" 


Benzo [j] fluoranthene 


3.0' 


16 


2.1' 


Benzo [k] fluoranthene 


LP 


16 


1.2" 


Benzofluoranthene 




16 


0.7" 


Benzofluoranthene 


0.7" 


16 


0.5" 


Benzo [e] pyrene 


1.8 P 


16 


1.3" 


Benzo [a] pyrene 


2.9" 


16 


1.7" 



(continued) 



Marijuana Smoke Condensate 

Table 1 (continued) 



91 



Class of compounds 


Amount 


Ref. 


Present in tobacco smoke? 


Pprvl f* n c 
r ci y iciic 


yj.y 


7rt 


No 

IN O 


pt rrwl npn 7r\n\ft"Atif> tw 
IVlCLlly lUCllZ,L>UyICllC *J1 


w. j 


7rt 
1 u 


w.z 


m pt n \7i Kpn v f\ 1 1 1 1 r\T*Q ntnpnp 
lllCLIly lUCHZ,UllLHJldllLllCllC 








IVlCLlly lUCllZ,UUylCllC Ul 


w.o 


1 u 


w.u 


lllCLIly lUCHZ,UllLHJldllLllCllC 








IVlCLlly lUCllZ,(JUylCllC Ul 


W.J 


7rt 
1 u 


W.J 


it-i pt r\ \7l npn v f~\ 1 1 n avq titnPTiP 
lllCLIly 1UC11Z,U11UU1 dllLlldlC 








Ix/I pt n^M npn vnin/rptip tw 
IVlCLlly !UCllZ,lJUylCllC Ul 


w.u 


1 u 


w.u 


m c»t n\rl npn v f a 1 1 n r>vci ntripnp 
lllCLIly lUCllAUllLUJldllLlldlC 








fit ri^M npn 7/"\t"\\7t*pnp tw 
IVlCLlly lUCllZ,UUylCllC \Jl 


w.u 


1 u 


w.u 


m fit n\rl npn v f a t 1 n r>vci ntripnp 
lllCLIly lUCHZ,UllLHJldllLllCllC 








fit ri^M npn 7nn^7i*pnp tw 
IVlCLlly lUCllZ,UUylCllC Ol 


1 9 e 


1 u 


w.u 


tY\ fit n\rl npn v f a 1 1 n r>vci ntnpnp 
lllCLIly lUCHZ,UllLHJldllLllCllC 








fit ri^M npn 7nni7fpnp tw 

IVlCLlly iuciiz,uuyiciic (Jl 




1 u 


w. / 


tY\ pt n\rl npn "7 f a t 1 1 1 r>vci ntnpnp 
lllCLIly lUCllAUllUtJl dllLlldlC 








l\/T pt n^M npn v/\n\/rpnp f"\v 
IVlCLlly lUCllZOUylCllC Ol 


IN O 


16 
1 u 


w.u 


m pthin npn v f~\T\ n avq ntnpnp 
lllCLIly lUCllZ,UllLHJld.llLllCllC 








pt ri^/l npn 7nn\/rpnp tw 
IVlCLlly lUCllZ,UUylCllC Ol 


w. / 


16 
1 u 


W.J 


m pth\n npn v f\ 1 1 n r>vci ntnpnp 
lllCLIly lUCllAUllLUJldllLlldlC 








pt ri^/l npn 7nn\7rpnp tw 
IVlCLlly lUCllzHJUylCllC Ol 


W.J 


16 


W.J 


m pth\n npn v f~\T\ n r\T*Q ntnpnp 
lllCLIly lUCllAUllLUJldllLlldlC 








pt n^/l npn 7r>n\/i"Pn(3 tw 
IVlCLlly lUCllzHJUylCllC Ol 


W.J 


16 


W.J 


m pth\n npn v f~\T \ n r\T*Q ntnpnp 
lllCLIly lUCllAUllLUJldllLlldlC 








pt n npn v^ahm rn n p fw 
IVlCLlly lUCllZOUylCllC Ol 


IN O 


16 
1 u 


w.z 


lllCLIly IDCllAUllLUJld-llLllCllC 








Methylbenzopyrene, 


U.J 


J 


CI Ae 

U.4 


euiyiDeiizopyrene, or 








ethylbenzofluoranthene 8 








Ethylbenzopyrene or 


CI Ae 

U.4 


J 


U.J 


ethylbenzofluoranthene 8 








Lh tn^rl npn 1 ? r\n\ 7~**p n p 

i_/LiiyiDciizupyrciic ur 


W.J 


16 


W.J 


ptrurl npn tat 1 1 1 nro t n p n ts\ ft 
CLliyiDCllZUllUUrallLllCllC* 








h 


U.J 


J 


INO 


, UlDeilZL«,(JaIlLIllaCcIie 


W.J 


16 
1 U 


INO 


h 


U.o 


J 


INO 


h 


1 r\f 
l.U 


1 A 
1 


U.J 


h 


U.J 


1 A 
1 


INO 


Dibenz[a,/i]anthracene or 


0.3' 


16 


0.6' 


dibenz[a,c]anthracene 








h 


0.4' 


16 


0.2' 


Benzo[g h ;']perylene 


0.7" 


16 


0.3' 


h 


0.4' 


16 


No 


Anthracene 


0.5' 


16 


No 


7 


0.5' 


16 


No 




0.2' 


16 


No 



(continued) 



92 



ElSohly and ElSohly 

Table 1 (continued) 



Class of compounds 



Amount 



Ref. 



Present in tobacco smoke? 



Diphenylacenaphthalene 
Quarterphenyl 



, Dibenzopyrene 
Dibenzopyrene 



0.4' 
0.5' 
0.4' 
0.5' 
0.3' 
OA' 
0.3' 
1.2' 



16 
16 
16 
16 
16 
16 
16 
16 



No 
No 
No 
No 
No 
No 
No 
No 



'Denotes its presence also in the polar neutral fraction. 

b One isomer. 

c Two isomers. 

rf Present only in tobacco. 

e jig/1 00 g cigarettes. 

'Could also be trimethyl or propyl. 

-Could also be dimethyl. 

''Compounds with molecular weight 276 can be any of the following: indeno[1 ,2,3-c cflpyrene; 
indeno[1 ,2,3,-c d\ fluoranthene; aceperylene; phenanthro[1 0,1 ,2,3-c d e f[ fluorene; acenaphth[1 ,2- 
oc]acenaphthylene; dibenzo[£>, m no] fluoranthene. Further possibilities are the benzo derivatives of 
acepyrylene and acefluoranthene. 

'Compounds with molecular weight 290 are methyl derivatives of those with molecular weight 276. 

ing from 10 to 29 mg/kg, the basic fraction caused a decrease in spatial locomotion, 
rearing behavior, and urination incidence. The authors concluded from these results that 
although the basic fraction of marijuana whole smoke condensate has pharmacological 
activity in mice, it offers little evidence for the presence of highly active compounds. 

4.2. Mutagenicity 

A study by Novotny et al. (24) has shown a possible chemical basis for the higher 
mutagenicity of marijuana smoke as compared to tobacco smoke. The total weights of 
polynuclear aromatic fractions containing three rings or more were significantly higher 
in MSC than in high-tar cigarette smoke condensate. The well known carcinogen 
benzo[a]pyrene was present in MSC by a 70% higher amount than in TSC. It was 
suggested that the pyrolysis products of A 9 -THC and other cannabinoids are major 
contributors to the formation of polynuclear aromatic hydrocarbons. MSC was shown 
to be mutagenic in strain TA 98 of the Ames Salmonella/microsome test (25), a short- 
term bioassay that estimates the mutagenic potential of some chemicals. The mutagens 
in MSCs required liver enzymes to be activated. The authors concluded that the basic 
fraction accounted for 76% of the recovered mutagenic activity. Further work on the 
mutagenic activity of extracts and smoke condensates of marijuana, Transkei home- 
grown tobacco, and commercial cigarette tobaccos was carried out (26) using Salmo- 
nella typhimurium strains TA 98, TA 100, TA 1535, TA 1537, and TA 1538, both 
with and without metabolic activation. No mutagenic activity was detected in the 
methylene chloride extracts of marijuana and tobacco, but all the smoke condensates 
exhibited mutagenicity with metabolic activation. The only strain not mutated by any 



of the pyrolyzates was TA 1535. Transkei tobacco pyrolyzate was most mutagenic, 
followed by marijuana, pipe, and cigarette tobacco. Mutagenicity was associated with 
the nitrogen content of the various products. 

The yield of MSC was 50% higher than that of cigarette and pipe tobacco, indi- 
cating a high carcinogenic risk associated with marijuana smoking. Bioassay results (3) 
showed that the acidic fractions were not significantly mutagenic, the neutral fractions 
were weakly mutagenic, but the basic fractions were significantly mutagenic. The 
constant draft base fractions were more mutagenic than puff mode basic fractions for 
both marijuana and tobacco, and the more polar subfractions (numbers 4-7) of the 
base fraction were more mutagenic than the less polar subfractions. 

4.3. Pulmonary Hazards 

The pulmonary effects associated with smoking marijuana and tobacco were 
examined in men (mean age 31.5 ± 7.1 years) by quantification of the relative burden 
to the lung of insoluble particulates (tar) and carbon monoxide from the smoke of 
similar quantities of marijuana and tobacco (27). Fifteen subjects who had smoked 
both marijuana and tobacco habitually for the previous 5 years were included in this 
study. Each subject's blood carboxyhemoglobin level before and after smoking and 
the amount of tar inhaled and deposited in the respiratory tract from the smoke of a 
single filter-tipped tobacco cigarette (900-1200 mg) and marijuana cigarettes (741- 
985 mg) containing 0.004% or 1.24% A 9 -THC were measured. Compared with smok- 
ing tobacco, smoking marijuana was associated with a nearly fivefold increment in 
the blood carboxyhemoglobin level, an approximate threefold increase in the amount 
of tar inhaled, and retention in the respiratory tract of one third more inhaled tar (p < 
0.001). Significant differences were also noted in the dynamics of smoking marijuana 
and tobacco, among them an approximately two-thirds larger puff volume, a one-third 
greater depth of inhalation, and a fourfold longer breath-holding time with marijuana 
than with tobacco (p < 0.001). These results may account for previous findings that 
smoking only a few marijuana cigarettes a day (without tobacco) has the same effect 
on the prevalence and chronic respiratory symptoms (28) and the extent of tracheo- 
bronchial epithelial histopathology (29) as smoking more than 20 tobacco cigarettes a 
day (without marijuana). These observations justify concern about the potential adverse 
pulmonary effects resulting from the long-term smoking of only a few marijuana ciga- 
rettes a day. 

4.4. Interaction With Estrogen Receptor 

Intraperitoneal administration of marijuana resin and smoke condensate to rat in 
doses of 10 and 20 mg/kg (in maize oil) affected their estrous cycle (30). Estrous was 
shortened with doses of both the resin and the smoke condensate, whereas diestrous 
was lengthened with the 20 mg/kg dose of the resin and both the 10 and 20 mg/kg 
doses of the smoke condensate. In addition, the administration of 20 mg/kg of either 
the resin or the smoke condensate resulted in a lengthening of the postestrous cycle. 

Sauer et al. (31) showed that crude marijuana extract at a concentration of 2.4 x 
10 5 M A'-THC (n = 6) competed with estradiol for binding to the estrogen receptor of 
rat uterine cytosol. MSC at an equivalent A 9 -THC concentration (n = 3) also competed 
with estradiol for its receptor. Pure A 9 -THC and 10 A 9 -THC metabolites failed to com- 



94 



ElSohly and ElSohly 



pete with estradiol for its receptor. Of several other cannabinoids tested, only canna- 
bidiol showed receptor-binding activity at very high concentrations (5.6 x 10 6 M; n = 2). 

Apigenin, a flavone present in marijuana, displayed high affinity for the estro- 
gen receptor at a concentration ranging from 5 to 50 x 10 1 M (n- 6). In vivo measure- 
ment of estrogen activity using uterine growth bioassay (immature rats) and crude 
marijuana extract administered subcutaneously in a dose containing 6.3-15.2 mg per 
day A 9 -THC failed to exhibit estrogenic or antiestrogenic effects. In conclusion, direct 
estrogenic activity of Cannabis extract could not be demonstrated in vivo. 

4.5. Inhibition of Dihydrotestosterone 
Binding to the Androgen Receptor 

MSC and two constituents of Cannabis, A 9 -THC and cannabinol, were tested for 
their ability to interact with the androgen receptor in rat prostate cytosol (32). The 
above-mentioned materials competitively inhibited the specific binding of 
dihydrotestosterone to the androgen receptor with a dissociation constant (Ki) of 2. 1 x 
10- 7 M for CBN, 2.6 x 10 7 Mfor A 9 -THC, and 5.8 x 10 7 M for MSC. The data indicate 
that the an ti androgenic effects associated with marijuana use result, at least in part, 
from inhibition of androgen action at the receptor level. 

References 

1. Patel, A. R. and Gori, G. B. (1975) Preparation and monitoring of marijuana smoke con- 
densate samples. Bull. Narc. 27, 47-54. 

2. Lerner, M. and Zeffert, J. T. (1968) Determination of tetrahydrocannabinol isomers in 
marihuana and hashish. Bull. Narc. 20, 53-54. 

3. Sparacino, C. M., Hyldburg, P. A., and Hughes, T. J. (1990) Chemical and biological 
analysis of marijuana smoke condensate. NIDA Research Monograph 99, 121-140. 

4. Gudzinowicz, B. and Gudzinowicz, M. (1980) Analysis of Drugs and Metabolites by Gas 
Chromatography '/Mass Spectrometry. Vol. 7. Natural, Pyrolytic and Metabolic Products 
of Tobacco and Marihuana, Marcel Dekker, New York. 

5. Schmeltz, I., Dooley, C. J., Stedman, R. L., and Chamberlain, W. J. (1967) Composition 
studies of tobacco. XXII. The nitromethane soluble, neutral fraction of cigarette smoke. 
Phytochemistry 6, 33-38. 

6. Novotny, M., Lee, M. L., and Bartle, K. D. (1974) The methods for fractionation, analyti- 
cal separation and identification of polynuclear aromatic hydrocarbons in complex mix- 
tures. J. Chromatogr. Sci. 12, 606-612. 

7. lones, L. A. and Foote, R. S. (1975) Identification of some acids, bases and phenols. /. 
Agric. FoodChem. 23, 1129-1131. 

8. Kettenes-Van Den Bosch, J. J. and Salemink, C. A. (1977) Cannabis XVI. Constituents 
of marihuana smoke condensate. J. Chromatogr. 131, 422-424. 

9. Zamir-ul Haq, M., Rose, S. I., Deiderich, L. R., and Patel, A. R. (1974) Identification and 
quantitative measurement of some N-heterocyclics in marijuana smoke condensates. 
Anal. Chem. 46, 1781-1785. 

10. Merli, F., Wiesler, D., Maskarinec, M. P., and Novotny, M. (1981) Characterization of 
the basic fraction of marijuana smoke condensate by capillary gas chromatography/mass 
spectrometry. Anal. Chem. 53, 1929-1935. 

11. Merli, F., Novotny, M., and Lee, M.L. (1980) Fractionation and gas chromatographic 
analysis of aza-arenes in complex mixtures. /. Chromatogr. 199, 371-378. 



Marijuana Smoke Condensate 



95 



12. Novotny, M., Strand, J. W., Smith, S. L., Wiesler, D., and Schwende, F. J. (1981) Com- 
positional studies of coal tar by capillary gas chromatography/mass spectrometry. Fuel 
60,213-230. 

13. Novotny, M., Merli, F., Wiesler, D., and Saeed, T. (1982) Composition of the basic frac- 
tion of marijuana and tobacco condensates: a comparative study by capillary GC/MS. 
Chromatographic! 15, 564-568. 

14. Fentiman, Jr., A. F., Foltz, R. L., and Kinser, G. W. (1973) Identification of 
noncannabinoid phenols in marihuana smoke condensate using chemical ionization/mass 
spectrometry. Anal. Chem. 45, 580-582. 

15. Maskarinec, M. P., Alexander, G., and Novotny, M. (1976) Analysis of the acidic frac- 
tion of marijuana smoke condensate by capillary gas chromatography-mass spectrom- 
etry. /. Chromatogr. 126, 559-568. 

16. Lee, M. L., Novotny, M., and Bartle, K. D. (1976) GC / Mass and nuclear magnetic 
resonance spectrometric studies of carcinogenic polynuclear aromatic hydrocarbons in 
tobacco and marijuana smoke condensates. Anal. Chem. 48, 405-416. 

17. Bartle, K. D., Lee, M. L., and Novotny, M. (1977) Identification of environmental poly- 
nuclear aromatic hydrocarbons by pulse Fourier-transform proton nuclear magnetic reso- 
nance spectroscopy. Analyst 102, 731-738. 

18. Novotny, M., Merli, F., Wiesler, D., Fencl, M., and Saeed, T. (1982) Fractionation and 
capillary gas chromatographic-mass spectrometric characterization of the neutral com- 
ponents in marijuana and tobacco smoke condensates. J. Chromatogr. 238, 141-150. 

19. Hood, L. V., Dames, M. E., and Barry, G. T. (1973) Headspace volatiles of marijuana. 
Nature (London) 242, 402-403. 

20. Friedrich-Fiechtl, J. and Spitetller, G. (1975) New cannabinoids. Tetrahedron 31, 479-487. 

21. Truitt, E. B. Jr., Kinser, G. W., and Berlo, J .M. (1976) Behavioral activity in various 
fractions of marihuana smoke condensate in the rat, in Pharmacology of Marijuana 
(Braude, M. C. and Szara, S., eds.), Raven, New York, pp. 2, 463-474. 

22. Johnson, J. M. (1981) The pharmacological activity of the acidic, basic, and polar-neutral 
fractions of marihuana whole smoke condensate alone, and in combination with A 9 -tet- 
rahydrocannabinol. Indiana University, Bloomington, IN, dissertation abstract 42(3), 983. 

23. Johnson, J. M., Lemberger, L., Novotny, M., Forney, R. B., Dalton, W. S., and 
Maskarinec, M. P. (1984) Pharmacological activity of the basic fraction of marijuana 
whole smoke condensate alone and in combination with A 9 -tetrahydrocannabinol in mice. 
Tox. Appl. Pharm. 72, 440-448. 

24. Novotny, M., Lee, M. L., and Bartle, K. D. (1976) A possible chemical basis for the 
higher mutagenicity of marihuana smoke as compared to tobacco smoke. Experientia 32, 
280-282. 

25. Busch, F. W., Seid, D. A., and Wei, E. T. (1979) Mutagenic activity of marihuana smoke 
condensates. Cancer Lett. 6, 319-324. 

26. Wehner, F. C, Van Rensburg, S. J., and Theil, P. G. (1980) Mutagenic activity of mari- 
huana and Transkei tobacco smoke condensates in the Samonella / microsome assay. 
Mutat. Res. 77, 135-142. 

27. Wu, T. C, Tashkin, D. P., Djahed, B., and Rose, J. E. (1988) Pulmonary hazards of 
smoking marijuana as compared with tobacco. N. Engl. J. Med. 318, 347-351. 

28. Tashkin, D. P., Coulson, A. H., and Clark, V. A. (1987) Respiratory and lung function in 
habitual heavy smokers of marijuana alone, smokers of marijuana and tobacco, smokers 
of tobacco alone, and non-smokers. Am. Rev. Respir. Dis. 135, 209-216. 

29. Gong, H., Fliegel, S., Tashkin, D. P., and Barbers, R. G. (1987) Tracheobronchial changes 
in habitual, heavy smokers of marijuana with and without tobacco. Am. Rev. Respir. Dis. 
136, 142-149. 



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30. Lares, A., Ochoa, Y., Bolanos, A., Aponte, N., and Montenegro, M. (1981) Effects of the 
resin and smoke condensate of Cannabis sativa on the oestrous cycle of the rat. Bull. 
Narc. 33, 55-61. 

31. Sauer, M. A., Rifka, S. M., Hawks, R. L., Cutler, G. B., Jr., and Loriaux, D. L. (1983) 
Marijuana: interaction with the estrogen receptor. /. Pharmacol. Exp. Ther. 224, 404- 
407. 

32. Purohit, V., Ahluwahlia, B. S., and Vigersky, R. A. (1980) Marihuana inhibits 
dihydrotestosterone binding to the androgen receptor. Endocrinology 107, 848-850. 



Chapter 5 



Pharmacology of Cannabinoids 

Lionel P. Raymon and H. Chip Walls 



1. Introduction 

Ever since the cloning of two distinct cannabinoid receptors and the discovery of 
lipids derived from arachidonic acid as endogenous ligands, cannabinoid pharmacol- 
ogy has received increased attention and yielded new insights in the understanding of 
the complex effects of smoking marijuana. Novel receptors offer the prospect of new 
therapeutics, and after decades of sparse research cannabinoid pharmacology is once 
again on the forefront of medical news. The use of molecular biology techniques, such 
as knockout mice, and the development of antagonists and agonists of the cannabinoid 
receptors are slowly unraveling a network of intricate physiological and neurological 
effects. 

1.1. Endogenous Ligands 

A family of lipids has been identified as the endogenous ligands to the cannab- 
inoid receptors. Two arachidonic acid derivatives were first isolated: an amide, 
arachidonoyl ethanolamide, or anandamide (1) and an ester, 2-arachidonoyl glycerol 
(2-AG) (2—4), Recently, a third derivative was isolated, an ether, 2-arachidonyl glyc- 
eryl ether, also known as noladin ether (5). These lipid compounds differ totally in 
structure from A 9 -tetrahydrocannabinol (THC), the main exogenous cannabinoid. Except 
for the notable absence of a nitrogen atom in THC, there is little to remind us of the 
eicosanoid- or prostaglandin-like structure of the anandamide family. 

Endocannabinoids are considered either neurotransmitters or neuromodulators: 
they have distinct synthetic pathways, are released from cells upon depolarization and 
calcium entry, and their synaptic action is rapidly terminated by reuptake and intracel- 
lular enzymatic degradation (Fig. 1). These requirements are met for anandamide and, 

From: Forensic Science and Medicine: Marijuana and the Cannabinoids 
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey 

97 



98 



Raymon and Walls 



N-APE 
PLD ^ 



|Ca 2+ 




IDG 



PLC 



Anandamide 2-AG 

I Transport 
± into cells 

Metabolism by FAAH 



Fig. 1. Metabolism of endogenous cannabinoids. N-APE, /V-arachidonyl phosphatidyl 
ethanolamine; PLD, phospholipase D; IDG, inositol-1 ,2-diacylglycerol; PLC, phos- 
pholipase C; 2-AG, 2-arachidonoyl glycerol; FAAH, fatty acid amide hydrolase. 

to a certain extent, 2-AG, but are still unclear for noladin ether. Anandamide and 2- 
AG are produced from cleavage of two different phospholipid precursors present in 
the cell membranes of neurons and immune cells in particular. Anandamide is synthe- 
sized from the membrane phospholipid Af-arachidonyl phosphatidylethanolamine by a 
phosphodiesterase called phospholipase D, an enzyme stimulated by depolarization- 
induced increase in intracellular Ca 2+ (5,6). The synthetic pathway is also indirectly 
stimulated by cyclic adenosine monophosphate (cAMP)/protein kinase A, indicating 
possible receptor-mediated mechanisms (7,8). Anandamide amounts of 10-50 pmol/g 
of brain tissue have been reported (6). 2-AG is mainly the product of phospholipase C 
digestion of inositol-1, 2-diacylglycerol and, interestingly, is much more abundant 
than anandamide, with amounts ranging from 2 to 10 nmol/g of tissue (9). The synthe- 
sis of 2-AG is also calcium-dependent (4). An interesting feature of anandamide and 
2-AG is the "on-demand" synthesis and release of these lipids, possibly not from 
vesicles, differentiating the endocannabinoids from classical neurotransmitters — hence 
the term "modulator" ( 10). Anandamide is then known to be transported into cells by 
carrier-mediated uptake, which does not depend on sodium or adenosine-5'-triphos- 
phate (ATP), another difference from classical neurotransmitters, but similar to the 
structurally related prostaglandin E 2 (ll). This transporter participates in the inactiva- 
tion of anandamide. Both anandamide and 2-AG are known to be rapidly hydrolyzed 
by the intracellular enzyme fatty acid amide hydrolase (FAAH) (6,12,13). 

Endocannabinoids may function physiologically as retrograde synaptic messen- 
gers (Fig. 2) (14,15). When a postsynaptic neuron is strongly depolarized, it synthe- 
sizes and releases endocannabinoids through a nonvesicular mechanism. These 
molecules, in turn, bind the presynaptic neuron at CB, receptors and inhibit its neu- 
rotransmitter release. It is a form of negative feedback. The chemical nature of the 
presynaptic neuron is important. If the release of an inhibitory transmitter like y- 
aminobutyric acid (GABA) is decreased, it is called in electrophysiology depolariza- 
tion-induced suppression of inhibition (DSI) and would result in exacerbation of 
postsynaptic transmission. If the release of an excitatory neurotransmitter like glutamate 



Pharmacology of Cannabinoids 



99 



GABA 



Anandamide 



\ Postsynaptic 
Depolarization 



DSI 



Presynaptic 
Neuron 



Antagonism 
by 

Rimonabant 



GLUTAMATE 



/ 



Anandamide 



Postsynaptic 4t 
Depolarization / 



DSE 



Fig. 2. Cannabinoid synapse: endocannabinoids are retrograde synaptic messengers 
through CB, receptors. GABA, y-aminobutyric acid; DSI, depolarization-induced 
suppression of inhibition; DSE, depolarization-induced suppression of excitation. 



is decreased, it is referred to as depolarization-induced suppression of excitation (DSE), 
and would diminish postsynaptic transmission. Several studies argue in favor of this 
physiological role of anandamide and other endogenous cannabinoids (16-18). Both 
DSI and DSE depend on rises in calcium and on G, proteins, which are also necessary 
for the synthesis and release of endogenous cannabinoids and a feature of their recep- 
tors. DSI and DSE are antagonized by rimonabant, a selective CB, receptor antago- 
nist. And finally, CB, stimulation inhibits GABA release from hippocampal 
interneurons (which synapse with the important pyramidal neurons) and glutamate 
from cerebellar basket cells (which synapse with Purkinje neurons). 

1.2. Cannabinoid Receptors 

Two cannabinoid receptors, CB, and CB 2 , have been cloned from various animal 
species, including humans (19-21). There is a shorter-isoform splice variant of CB,, 
CB, A , with no known function, and recent reports indicate other types of receptors yet 
to be cloned. Cannabinoid receptors belong to the superfamily of G protein-linked 
receptors (14,15,22). These receptors are characterized by 7-transmembrane domains, 
an extracellular NH 2 terminus, and an intracellular COOH terminus. Once bound, G 
protein-linked receptors activate a G protein. A G protein is a trimeric protein (a- and 
Py-subunits), which uses guanosine triphosphate as a source of energy to "do its job," 
i.e., change the activity of enzymes downstream in the signal transduction pathway 
(Fig. 3). It therefore allows signal transduction from the outside of the cell, where the 
ligand binds to the receptor, to the inside of the cell, where molecular changes in key 
target proteins will result in a biological response. Cannabinoid receptors are said to 



100 



Raymon and Walls 



Stimulation 



1 




1 



JJ. Adenylcyclase 



1 



4 cAMP 



1 



I), Protein Kinase A 



1 



Gene Expression 



Enzyme Activity 



Ion Channel 



Fig. 3. CB, receptors are G r coupled: an inhibitory effect on cellular function is 
expected from receptor stimulation. 

be G| coupled: a G l protein, when activated, inhibits the enzyme adenylate cyclase. It 
is the a subunit that interferes with adenylate cyclase. The (3y dimer can regulate other 
enzymes such as mitogen-activated protein kinase (MAPK) and phosphatidylinositol- 
3-kinase (PI3K) or directly modify the activity of ion channels. Adenylate cyclase in 
turn no longer breaks ATP to form the second messenger cAMP. The result of cannab- 
inoid receptor stimulation is therefore a decreased concentration of intracellular cAMP. 
cAMP is referred to as the second messenger (the drug/endogenous ligand binding to 
the receptor being the first messenger). cAMP plays major roles inside a cell: through 
protein kinase A it can phosphorylate a number of proteins, and phosphorylation of 
proteins changes their activity. An enzyme may be turned on or off by phosphoryla- 
tion, altering metabolic pathways; an ion channel may open or close, changing the 
membrane potential status of an electrical cell; importantly, transcription factors (pro- 
teins that control gene expression such as cAMP response element-binding protein) 
may be activated and modify the proteins actually expressed by the cell. Whereas 
changes in gene expression might take days to fully take place, opening or closing an 
ion channel would have immediate effects (seconds or less). 

Overall, the decreased cAMP in the cells expressing CB, or CB 2 receptors would 
tend to result in an inhibition of function. A rapid effect of CB[ stimulation seems to 
be mediated through a decreased phosphorylation of A-type potassium channels, 
resulting in their opening (23). When a potassium channel is opened, the net force 
(electrical and concentration gradient) results in an efflux of potassium, and the loss 
of positive charges from the cell renders the cell less excitable (hyperpolarized). A 
number of calcium channels are closed by the same mechanism, particularly neuronal 
N-type, resulting in a decreased excitability also (24). Most CB[ receptors are found 
presynaptically and can modulate neurotransmitter release through presynaptic inhi- 
bition. Decreased release of glutamate, GABA, norepinephrine, dopamine, serotonin, 



Pharmacology of Cannabinoids 



101 



and acetylcholine in slices of hippocampus, cerebellum, and neocortex has been reported 
either from direct observation or indirectly, through electrophysiological methods (25). 
Other key proteins are regulated through signal transduction from cannabinoid recep- 
tors. They include focal adhesion kinase, which is phosphorylated on tyrosine resi- 
dues and plays a role in synaptic plasticity (26), and PI3K activation by (3y-subunits of 
Gj, resulting in phosphorylation of Raf-1 and then phosphorylation of MAPK to acti- 
vate it. In turn, MAPK can activate phospholipase A 2 and trigger the arachidonic acid 
cascade and production of prostaglandins (27), and can decrease growth factor recep- 
tor synthesis in certain tissue, a basis for antiproliferative action of cannabinoids (28). 
PI3K is also biochemically associated with mediation of insulin-like effects with 
upregulation of glucose transporter 4 (insulin-dependent glucose uptake in skeletal 
muscle and adipose tissue), stimulation of glycogen synthesis, and glycolysis (liver 
cells). These latter effects would require the presence of receptors to anandamide on 
the appropriate target cells. 

Distribution of receptors and the role of the cells affected can give insight into 
the pharmacology of agonists and antagonists of these receptors, and correlation 
between observed effects and expected effects can be theorized. CB, has been mapped 
mainly to the central nervous system (CNS) and peripherally to sensory neurons and 
the autonomic nervous system. CB, receptors are strictly peripheral and are found 
particularly on mature B cells and macrophages and on immune-related tissues such 
as tonsils and spleen. In the CNS, CB, receptors have been mapped in various animal 
species and in humans using autoradiography and immunohistochemical mapping tech- 
niques (29-31). Whereas CB, receptors correlate poorly with anandamide distribu- 
tion, they are found in brain regions rich in the degradative enzyme FAAH. Interestingly, 
FAAH is found postsynaptically and CB, receptors are found presynaptically, an ana- 
tomical arrangement that correlates well with the role of endogenous cannabinoids as 
retrograde synaptic messengers (32). The highest densities are found in the cerebral 
cortex, particularly the association cortex, in the basal ganglia and cerebellum, and in 
the limbic forebrain (particularly hypothalamus, hippocampus, and anterior cingulate 
cortex). They are relatively absent from brainstem nuclei. 

Cannabinoids affect cognitive and motor functions. Their subjective effects are 
well documented by chronic users and include enhancement of senses, errors in time 
and space judgment, emotional instability, irresistible impulses, illusions, and even 
hallucinations. Objective effects have been measured and studied, and decreased psy- 
chomotor performance, interference with attention span, and loss of efficiency in short- 
term memory are classically reported in the literature. Cannabinoids also have a number 
of peripheral effects, notably vasodilatation, tachycardia, and immunosuppressant prop- 
erties. This chapter explains the neurophysiological and anatomical bases of these 
disorders and correlate them with what is known of the cannabinoid receptors. 

2. Effects of Cannabinoids on Motor Coordination 

2.1. Cortical Areas 

Complex brain functions such as cognition, language, sexuality, sleep/wakeful- 
ness, emotions, and memory require constant information processing. Of the human 
cortex, 75% is association cortex (Fig. 4). The ability to attend, identify, and plan a 



102 



Raymon and Walls 



ASSOCIATION 
CORTEX 



Plans Appropriate 
Behavioral Response 



Attends to 
Complex Stimuli 



ASSOCIATION 
CORTEX 



ASSOCIATION 
CORTEX 




Identifies 
Stimuli 



Fig. 4. Role of brain cortical areas: after identification of a stimulus by temporal 
regions, parietal areas attend to the stimulus, and frontal areas plan the appropriate 
behavioral responses. CB, receptors are dense in all cortical areas. 



meaningful response to external or internal stimuli depends to a large extent on that 
association cortex, and one could define cognition as the processes by which we come 
to know and understand the world. Most inputs to the association cortex come from 
other cortical areas (hence the name "association"), either on the same hemisphere or 
the opposite one. Classically, three big areas are described. Imagine a driver and the 
sound of a horn — the temporal association cortex identifies the stimulus. The infor- 
mation is then relayed to the parietal association cortex, which decides whether to 
attend to the stimulus or not. In turn, the processed information is sent to the frontal 
association cortex for planning of appropriate behavioral response. The remainder 
(25%) of the cortical areas is subdivided into the primary sensory cortex, which receives 
inputs from the periphery by the intermediate of the thalamus, and the motor cortex, 
which receives inputs from the basal ganglia and the cerebellum, also through the 
thalamus. Two structures, the corpus callosum and the anterior commissure, allow 
communication from one side of the brain to the other. 

Much of our understanding of brain regional neurophysiology comes from patho- 
logical lesions and their observation. Often, a drug, by altering physiological systems, 
can mimic in part what the pathology describes. For example, lesions of the temporal 
lobes result in recognition deficits. The patient has difficulty recognizing, identifying, 
or naming familiar objects. Syndromes of temporal lobe lesions are called agnosias, 
such as prosopagnosia, in which the patient cannot name things. Lesions of the pari- 
etal lobes lead to attention and perception deficits, often referred to as contralateral 
neglects — the patient fails to report, respond, or orient to a stimulus presented to the 



Pharmacology of Cannabinoids 



103 



Association Motor 
Cortex Cortex ~ 



PLANNING EXECUTION 




Spinal Cord 
I 

Muscles 

Fig. 5. Role of basal ganglia and cerebellum in the programmation of movements: 
whereas the basal ganglia allows the initiation of movement, the cerebellum controls 
the ongoing aspects of it. CB, receptors are highly expressed in the basal ganglia and 
cerebellum. 



side of the body or visual space opposite the brain lesion. Finally, lesions of the fron- 
tal lobes alter the individual's personality, the ability to plan a behavior in relationship 
to the environment, and to use memories as a guide to appropriateness of behavior in 
various situations. 

CB, receptors are particularly dense in all cortical areas (31), particularly the 
cingulate cortex (see Section 3), and inhibition of evoked release of a number of neu- 
rotransmitters would result in cognitive impairment such as perception, attention, and 
behavioral deficits. It is difficult to ascribe specific deficits because of the complexity 
of the neural wiring in cortical regions. 

2.2. Basal Ganglia and Cerebellum 

The basal ganglia and the cerebellum interact with the cortex through a series of 
feedback circuits. The basal ganglia, a group of midbrain nuclei, are involved mainly 
with the initiation and execution of a movement, whereas the cerebellum tends to 
modulate ongoing movement (Fig. 5). Again, pathology clearly describes the role played 
by these structures in motor coordination. The most relevant disorders are the 
dyskinesias, or abnormal movements. Basal ganglia degeneration results in move- 
ment disorders such as Parkinson's disease (selective destruction of dopamine-con- 
taining neurons) and Huntington's disease (selective destruction of GAB A 
interneurons). Parkinson's disease is classically associated with the triad of resting 
tremors, muscle rigidity (cogwheel-like), and slowness of movement (bradykinesia, 
with a festinating gait). Huntington's dyskinesias tend to be the opposite of Parkinson's, 



104 



Raymon and Walls 



with excessive initiation of unwanted movements. Cerebellar degeneration is associ- 
ated with asynergy, the inability to achieve a properly timed and balanced activation 
of the muscles during movement. Asynergy causes a decomposition of movements, 
resulting in the move going too far or falling short (dysmetria — the error is overcom- 
pensated). The gait becomes uncertain in cerebellar damage, with the feet placed far 
apart and the steps overshooting (ataxia), and it is no longer possible to make move- 
ments in rapid succession (dysdiadochokinesia). There are corresponding disturbances 
of speech and vision. In cerebellar injuries, the tremors do not appear at rest, but rather 
occur during movement (intention tremors), and the muscle tone tends to be low, with 
weak muscles that become tired easily. These are the kind of disturbances often seen 
at the roadside in field sobriety exercises such as one-leg-stand, walk-and-turn, and 
the finger-to-nose test when a driver is under the influence of drugs such as marijuana. 

CB, receptors are highly expressed in the basal ganglia and the cerebellum. To 
understand the possible effect of THC binding to these receptors, some well-estab- 
lished neuronal connections between these structures are relevant to review prior to 
correlation with CB[ receptor distribution. The basal ganglia illustrates well the con- 
cept of disinhibition at the neuronal level. Two key pathways are described: the direct 
and the indirect pathways (Figs. 6 and 7). 

The association cortex and substantia nigra send excitatory impulses to the cau- 
date putamen. The excitation comes from the neurotransmitter released at these syn- 
apses, glutamate, which is the major excitatory amino acid transmitter in the human 
brain. This in turn activates a GABA interneuron, GABA being the major inhibitory 
neurotransmitter in the human brain. The release of GABA occurs in the globus pallidus 
(internal segment) and at the synapse of another GABA neuron. This latter neuron is 
called a tonic neuron. It is always active, releasing GABA in motor nuclei of the thala- 
mus (ventral lateral and anterior), resulting in inhibition of the thalamic excitatory 
outflow to the premotor cortex. The stimulation of the GABA interneuron turns off 
(inhibits) the tonic GABA neuron, resulting in disinhibition of the excitatory thalamic 
outflow to the premotor cortex: as a result, movement is initiated. Electrophysiology 
has shown that electrical activity in the tonic GABA neuron ceases before execution 
of a complex movement and resumes once the movement is underway. 

The indirect pathway is more complex than the direct pathway. The tonic GABA 
neuron from the internal segment of globus pallidus is also under excitatory control 
from a glutamate excitatory interneuron from the subthalamic nucleus. Under normal 
conditions, this glutamate interneuron is inhibited by a tonic GABA neuron that arises 
from the globus pallidus external segment. In the indirect pathway, excitatory inputs 
from the associative cortex turn on a GABA interneuron from the caudate-putamen. 
This prevents the tonic GABA neuron from the globus pallidus from firing and 
disinhibits the glutamate interneuron from the subthalamic nucleus. The firing of the 
glutamate interneuron results in stronger inhibitory tone from the tonic GABA neuron 
projecting to the thalamus and prevents movement from being initiated. An alterna- 
tive with the opposite effects arises from dopamine-containing inhibitory neurons from 
substantia nigra impacting the same GABA interneuron as the cortical excitatory input. 
The indirect pathway antagonizes the direct pathway and therefore allows fine control 
of the excitatory outputs to motor and premotor cortices, allowing coordinated move- 
ments to occur. 



Pharmacology of Cannabinoids 



105 



Association 

Cortex Premotor 




Fig. 6. Initiation of movement: the direct pathway. Neurons in dashed line are 
inhibitory, containing principally y-aminobutyric acid (GABA); neurons in solid line 
are excitatory, containing principally glutamate. A tonic neuron is a neuron that 
always fires. CB, receptors are found on GABA interneurons and glutamate projec- 
tion neurons, leading to complex motor effects. 



Association 

Cortex Premotor 




Dopamine'*. TONIC Movement 

Substantia 
Nigra 



Fig. 7. Initiation of movement: the indirect pathway. Neurons in dashed line are 
inhibitory, containing principally y-aminobutyric acid (GABA); neurons in solid line are 
excitatory, containing principally glutamate. A tonic neuron is a neuron that always 
fires. The indirect pathway opposes itself to the direct pathway, allowing coordination 
of movements. Notice the role of nigral dopamine in movement initiation. 



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Fig. 8. Cerebellar pathways: CB, receptors are found on virtually all principal 
glutamate or y-aminobutyric acid inputs to cerebellar Purkinje cells. 



In the basal ganglia, CB, receptors are found on GABA medium spiny projection 
neurons (interneurons), particularly at the axon terminal. CB, receptors are also found 
on glutamate projection neurons, and whereas GABA interneurons are inhibitory, 
glutamate neurons are excitatory. The effect on movement initiation is therefore com- 
plex, depending on which system is inhibited by CB, receptor stimulation. Basal motor 
activity is regulated in part by CB, receptors, and a general inhibition of movement 
and tremors has been reported in animal experiments and human observations. 
Decreased glutamate release from the subthalamic neurons (indirect pathway) would 
result in this inhibition, as well as a decreased release of GABA from interneurons of 
the direct pathway or from the GABA tonic neurons of the globus pallidus projecting 
to the subthalamic nucleus (indirect pathway). 

The wiring to and from the cerebellum is analogous to the ones in the basal ganglia 
(Fig. 8). The cerebellum receives three kinds of information: from the cortex, from ves- 
tibular nuclei in the brainstem, and from the spinal cord. The impulses come through 
excitatory climbing and mossy fibers. Climbing fibers are important because they adjust 
the flow of information that reaches the Purkinje cells and influence motor learning by 
inducing plastic changes in the synaptic activity of Purkinje neurons. The cerebellum 
has a unique output, the Purkinje neurons, which are GABA-containing neurons. They 
send information through inhibitory control of deep cerebellar relay nuclei, which in 
turn inform the thalamus and then the cortex, giving the cerebellum access to corticospi- 
nal projection neurons. This allows the cerebellum to organize the sequence of muscular 
contractions in complex ongoing movements and finely regulate them. 



Pharmacology of Cannabinoids 



107 



CB, receptors are found on virtually all the principal glutamate and GAB A inputs 
to cerebellar Purkinje cells and, through inhibition of glutamate or GABA release, can 
exert complex motor effects. 

Rodriguez de Fonseca et al. (33) have reviewed the literature related to motor 
effects of Cannabis on animals and humans. Studies of locomotor activities (LMA) in 
mice have showed dose-dependent effects of THC, with a decreased LMA at doses of 
0.2 mg/kg and increased LMA at doses of 1-2 mg/kg and eventually catalepsy at 
doses in excess of 2.5 mg/kg. These changes could relate to differential sensitivities of 
neuron populations to CB, stimulation, resulting in different levels of inhibition of 
excitatory glutamate or inhibitory GABA release. Human studies have corroborated 
these results: impaired balance (34) and problems with tracking and pursuit of a mov- 
ing point of light (35). Importantly, often unpublished Drug Recognition Officer reports 
filled out by law-enforcement experts and collected in a number of forensic toxicol- 
ogy laboratories anecdotally support the impaired locomotor functions of humans un- 
der the influence of Cannabis. Some interesting new studies have used knockout mice 
models. A knockout mouse is an animal model in which a fertilized ovum from a 
pregnant female mouse (rat) has been genetically altered in a way to delete a specific 
gene and is then reimplanted to allow the pregnancy to continue. The offspring is then 
referred to as a knockout animal because in every nucleated cell a specific gene is 
missing. The lack of expression of the protein encoded by the missing gene results in 
symptoms that can be carefully correlated with the role of this protein in the wild 
animal. However, it is impossible to predict any effects from compensatory changes 
in expression of other genes as a result of the deletion. CB, knockout mice have been 
developed (36) and have been extensively studied. But conflicting results have been 
reported: a decreased basal activity in these animals suggests that tonic activation of 
CB, receptors actually promote movements. On the other hand, Ledent et al. (37) 
showed increased locomotor activity in a different strain of knockout mice (CD1 vs 
C57BL/6J). The availability of a selective antagonist of CB1 receptors, rimonabant 
(SR141716A), also contributed some information on the effects of THC on psychomo- 
tor movement, with an increased LMA noted in mice treated with the antagonist (38). 

3. Effects of Cannabinoids on the Limbic System 

A major function of the CNS is to keep the internal environment stable and con- 
stant (homeostasis). The limbic system in general and the hypothalamus in particular 
are vital for this through three major, closely related processes: the secretion of hor- 
mones, the central control of the autonomic nervous system, and the development of 
emotional and motivational states. The limbic system is the primitive brain ("reptil- 
ian" brain) and consists of deeply seated brain structures: the hippocampus, communi- 
cating through the fornix with mamillary bodies (close to the hypothalamus), themselves 
linked to the anterior thalamus and feeding and receiving information from associa- 
tion areas and frontal cortex, critical in memory making and retrieving; the olfactory 
bulbs and the amygdala, instrumental in behavior and receiving highly processed sen- 
sory information; and the limbic system, with its own cortex, the cingulate cortex, 
wrapped around these structures and very much involved in behavior. The limbic sys- 



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Association 
Areas 



FRONTAL 
LOBE 



\ 




LIMBIC 

SYSTEM 



Expression of Behavior 



Control of Hypothalamus: 
Homeostatic functions 
Circadian rhythm 
Reproduction 



Hypothalamus 



Brainstem 



Memory: 

Declarative, not procedural 



Fig. 9. The limbic system and its connections. 



tern receives information from all association cortex areas of the brain and communi- 
cates with the frontal lobe, the hypothalamus, and the brainstem. Hypothalamic and 
limbic neurons interact with the reticular formation and the neocortex for mainte- 
nance of a general state of awareness (arousal). The roles of the limbic system can be 
simplified to three major tasks: the expression of behavior; the control of the hypo- 
thalamus (homeostatic functions, circadian rhythm, and reproductive behavior and 
control); and memory (Fig. 9). 

3.1. Hippocampus and Memory Impairment 

Classically, memory is associated with the hippocampus. But in reality, the basal 
ganglia and the cerebellum are also involved in formulating and retrieving memories. 
There are two different types of memories, referred to as declarative and procedural. 
Declarative memory is the storage and retrieval of material available to the conscious 
mind. It is encoded in symbols and can be expressed as language (hence, declarative), 
for example, remembering someone's name, a phone number, or an appointment date. 
The hippocampus and association cortex are critical in declarative memory. Proce- 
dural memory is not available to the conscious mind. It is about things we do not think 
of. Such memory involves skills and associations that are occurring unconsciously, 
for example, riding a bicycle, driving a car, or playing a piece of piano music. When 
we perform a complex action, we do not need to be conscious of a particular memory, 
and even thinking about it may actually inhibit the ability to perform this complex 
action smoothly. Procedural memory involves the basal ganglia, the cerebellum, and 
the motor cortex. 

Another way to classify memory is based on a temporal scale: short-term memory 
occurs in hippocampal and related structures of the limbic system; long-term memory 



Pharmacology of Cannabinoids 



109 



storage is not clearly located in a specific structure, but rather seems to involve corti- 
cal areas, such as the temporal cortex for the memory of faces or Wernicke's area for 
the memory of words. Pathology again has revealed a great deal about the importance 
of the hippocampus and memory formation: in medical history, an epileptic patient 
had the tips of both temporal lobes removed by surgery and as a result was incapable 
of remembering anything new, but had no change in intelligence and could remember 
things that occurred prior to the operation (anterograde amnesia). 

Cannabis use in humans has long been known to impair short-term memory in 
humans (39,40). Most of the tests used in humans have shown deficits in declarative 
memory. In animals, deficits in short-term memory have also been described, particu- 
larly in procedural memory (spatial learning tasks; ref. 41). Both THC and anandamide 
cause these effects, and they are reversed by the antagonist rimonabant, suggesting 
the involvement of CB, receptors (42,43). At the cellular level, the hippocampus has 
clearly defined pyramidal cells, which contain glutamate and communicate extensively 
with basket cell interneurons, which contain GAB A. CB, receptor distribution is high 
in the hippocampus on both types of neuron (44). THC and other CB, agonists likely 
decrease the release of GAB A and glutamate at hippocampal synapses, interfering 
with the phenomenon of long-term potentiation, a critical synaptic event associated 
with engraving recent event in short-term memory. Supporting this are results from 
the study of CB, knockout mice: the absence of CB, receptors resulted in increased 
long-term potentiation (45) and increased memory (46). Further, rimonabant was shown 
to improve memory in rodents (47). These data suggest that CB, receptor stimulation 
inhibits the mechanisms by which short-term memorization occurs. 

3.2. Amygdala and Behavioral Effects 

The amygdaloid complex comprises basolateral and corticomedial nuclei. They 
are intrinsically connected. Afferents come from virtually all brain areas, as do efferents. 
Damage to the amygdala in humans is called the Kluver-Bucy syndrome: the patient 
can no longer recognize objects by sight, touch, or hearing (visual, tactile, and audi- 
tory agnosia) and is docile, eats excessively (sometimes objects that are not food), and 
has inappropriate behavior, particularly hypersexuality. Stimulation of the amygdala 
in animals results in aggressive or defensive behavior. CB, receptors are found on 
GAB A neurons of the amygdala (48). If the effects of GAB A at the level of the amygdala 
are to decrease the excitability of efferent neurons, CB, stimulation at this level may 
well result in aggressive behaviors. Interestingly, Cannabis psychosis has been re- 
ported in the literature (49,50), and cannabis users have sometimes been hospitalized 
and met the criteria for schizophrenia. 

3.3. Hypothalamus and Neuroendocrine Effects 

The hypothalamus is the principal brain region controlling feeding and regula- 
tion of body weight. Several neurotransmitters are involved in the control of food 
intake. Serotonin and norepinephrine tend to inhibit feeding; peptides such as NPY 
and orexins A and B tend to stimulate eating behaviors, whereas cocaine- and amphet- 
amine-regulated transcripts and proopiomelanocortin-derived peptides are anorectic; 
hormones such as insulin and leptin also play a role, with leptin preventing body weight 
gain and insulin increasing body weight. Endogenous cannabinoids participate in the 



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control of food intake, in part through interaction with leptin. Animals with defective 
leptin signaling are obese and have been found to have more anandamide and 2-AG 
than normal animals (51). Giving leptin to normal rats results in decreased levels of 
endogenous cannabinoids. Further, rimonabant reduces food intake and causes weight 
loss, and CB, knockout mice eat less than wild-type mice. Cannabis use in humans is 
associated with the stimulation of appetite. Dronabinol, a US Food and Drug Admin- 
istration-approved oral formulation of THC, has been successfully used in the treat- 
ment of AIDS wasting syndrome. Animals who are receiving THC or anandamide 
also eat more, and this effect is blocked by rimonabant, which is currently being 
investigated as an appetite suppressant (51-53). Although there are relatively low den- 
sities of CB, receptors in the hypothalamus, all nuclei seem to show binding by auto- 
radiography, particularly in the medial preoptic area and in the arcuate nucleus (54). 
Besides central effects of cannabinoids on food intake, there is also evidence of a 
peripheral metabolic action of CB, receptors. Rimonabant was shown to decrease 
hyperinsulinemia in obese rats and increase the gene expression of adiponectin 
(adipocyte complement-related protein, or Acrp30; ref. 55). Adiponectin is expressed 
in the adipose tissue, induces fatty acid oxidation, and causes weight reduction and 
increased insulin responses. If rimonabant is truly an antagonist, this suggests a meta- 
bolic role for elusive peripheral CB, receptors. 

THC influences many other hypothalamic controlled neuroendocrine responses. 
Through decreased norepinephrine release, CB, stimulation results in decreased gona- 
dotropin-releasing hormone and suppression of luteinizing hormone and follicle-stimu- 
lating hormone release by the pituitary as a result (56). There are also reports of 
decreased growth hormone release and decreased prolactin release (57), probably 
resulting from decreased dopamine release and effects on other anterior pituitary hor- 
mones under hypothalamic control. 

A related central effect is the antiemetic effects of THC and analogs. Nabilone is 
a synthetic cannabinoid Food and Drug Administration-approved for chemotherapy- 
induced nausea and vomiting (like dronabinol), but its use has long been supplanted 
by the serotonin 5HT 3 receptor antagonist family of drugs. Interestingly, there are CB, 
receptors in the area postrema, part of the nucleus tractus solitarius, which represents 
the "vomiting" center in the medulla (54). Neurons in the area postrema are serotoner- 
gic and dopaminergic, with stimulation of D 2 -like receptors or 5HT 3 receptors result- 
ing in vomiting. It is possible that CB, stimulation results in decreased release of 
dopamine or, as suggested in rat studies, of serotonin (58). 

4. Cannabinoids and Analgesia 

Pain pathways are described at three levels: in the periphery, where it originates; 
at the level of the spinal cord, where some control "gating" the transmission of pain 
exists; and in the CNS, particularly at the level of the periaqueductal gray. CB, recep- 
tors are found on peripheral nerves (59), and injection of anandamide into tissues 
swollen from carageenan-induced inflammation has been shown to reduce pain in rats 
(60). But there is much more evidence for a spinal and a central site of action of 
cannabinoids. To understand better some of the sites and mechanisms of action of 
cannabinoids, a simplified pain pathway model is presented in Figs. 10 and 11. 



Pharmacology of Cannabinoids 



111 



GABA 
"On" 



A' 



,,•■■■0 Opiate Neuron 

Cannabinoid 
Neuron? 



©* 





PAIN 


RVM 






Projection 




Neuron 


Spinal Cord 



Sensory 
Neuron 



Fig. 10. Neurotransmitters and spinal modulation of pain: whereas serotonin (5HT) 
abolishes pain transmission, y-aminobutyric acid (GABA) increases it by inhibition of 
the 5HT neuron. Cannabinoids may modulate pain transmission by inhibiting the 
firing of this GABA neuron, in a way similar to opiates. RVM, rostral ventrolateral 
medulla. 



Periventricular 
Gray 



1 



Periaqueductal 
Gray 



Raphe Nuclei 
N. Reticularis 
Paragigantocellularis 



5HT 



Dorsal Horn 



1 



Dorsolateral 
Pontomesencephalic 
Tegmentum 



Locus 
Coeruleus 



NE 



Fig. 1 1 . Modulation of pain by descending pathways. Whereas serotonin (5HT) 
inhibits pain transmission, norepinephrine (NE) stimulates it. An inhibition of NE 
release through CB, receptors could also explain some of the analgesic effects of 
cannabinoids. 



112 



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Pain transmission ascends through the spinal cord to the thalamus and then to 
somatosensory cortical areas and prefrontal cortex. The main pathway carrying noci- 
ceptive stimuli to the brain is the prominent spinothalamic tract. Figure 1 1 shows that 
the synapse between the peripheral sensory neuron (first-order neuron) and the sec- 
ondary projection neuron is under the control of a serotonin-descending neuron, which 
abolishes the transmission of pain to higher centers. The serotonin neuron is itself 
under the inhibitory control of a GABA interneuron. When GABA is released, the 
serotonin neuron is turned off, and pain transmission occurs. Interneurons communi- 
cate the ascending information to the reticular formation of the medulla, the 
periaqueductal gray (PAG) of the midbrain, and the periventricular nucleus of the 
hypothalamus. These structures in turn modulate pain transmission through descend- 
ing pathways, synapsing with all the above structures. These pathways have been 
extensively studied as a site for opiate action and are now relevant as a site of action of 
cannabinoids as well. For example, the PAG stimulates directly raphe nuclei, where 
serotonin-containing neurons can inhibit pain transmission (Fig. 12). The PAG also 
sends signals to the dorsolateral pontomesencephalic tegmentum (DLPMT) and the 
periventricular nucleus of the hypothalamus. The DLPMT is the beginning of the sec- 
ond major descending pathway, which involves norepinephrine and locus coeruleus 
neurons. But unlike serotonin, norepinephrine is a nociceptive substance in this modu- 
latory pathway: it causes pain. 

Any stimulation of the serotonin-descending pathway, such as through GABA 
release inhibition, or any inhibition of the noradrenergic-descending pathway, such as 
through decreased synaptic release of norepinephrine, would result in analgesia. 

Evidence shows that THC and cannabinoids prevent pain transmission when in- 
jected directly into the spinal cord, the brainstem, or even the thalamus (61). CB, 
receptors are very dense in specific layers of the dorsal horn of the spinal cord, where 
peripheral sensory afferents synapse with second-order neurons to transmit pain to 
higher centers (62,63). Further, pain itself causes the release of anandamide in the 
PAG, suggesting that endogenous cannabinoids physiologically play a role in the 
modulation of pain signaling (64). Because these pathways are generally associated 
with opiate pharmacology, it was important to investigate if opiate receptors were 
involved. Results suggest a parallel but distinct neural pathway for cannabinoids and 
opiates. For example, if morphine and THC were given together, an additive or syner- 
gistic effect would be expected. Both rimonabant and naloxone could block this effect, 
indicating the participation of CB! and opiate receptors, respectively (65). Opiates are 
known to decrease GABA release at the level of the serotonergic neuron, resulting in 
inhibition of an ascending pain pathway. It is possible that cannabinoids may decrease 
GABA release at the same level, but through a distinct CB, receptor effect. Some 
studies suggest an effect on norepinephrine release because intrathecal injection of 
yohimbine, an a 2 antagonist that would increase the synthesis and release of norepi- 
nephrine at the synaptic cleft, blocks THC-induced analgesia (66). It is interesting to 
note that CB , and a 2 receptors are negatively coupled to c AMP production through G l 
proteins. 

CB , knockout mice bring an interesting development in understanding the com- 
plexity of pain modulation by THC and endogenous cannabinoids: anandamide con- 



Pharmacology of Cannabinoids 



tinues to cause analgesia in these animals in spite of the absence of CB, receptor 
expression, whereas THC does not (67). The discrepancy may be explained by a novel 
cannabinoid receptor or through anandamide's binding to the vanilloid receptor VR,, 
which is present in primary afferent sensory neurons (68,69). VR, is a capsaicin-sen- 
sitive cationic channel (Na + , Ca 2+ , K + ), and anandamide is proposed to be the endog- 
enous ligand (70). Other stimuli for the channel are heat and protons, and VR, plays a 
role in the modulation of intracellular calcium, which in turn regulates neurotransmit- 
ter release. This new pharmacology is at the center of a debate regarding legalization 
and the use of Cannabis products in the management of pain as well as in a number of 
inflammatory disorders. 

5. Cannabinoids and Addiction 

Cannabis remains the most commonly used illicit drug of abuse in the United 
States and probably in the world. A typical Cannabis high starts with tingling of the 
body and head, progresses to dizziness and a quickening of mental associations with 
sharpened senses, heightened perception, increased appetite, and a distortion of the 
sense of time, causing it to go faster, and ends with calm, drowsiness, and eventually 
sleep (15). CB, receptors are central to the intoxicating effects, as evidenced by the 
blockade of those effects by rimonabant (71 ). Dopamine plays a major role in reward, 
and most drugs abused directly increase dopamine levels in the mesocorticolimbic 
pathways involved with reinforcement and pleasure (72). The neural substrates of 
reward involve the medial forebrain bundle (MFB) and its connected structures, in- 
cluding most of the brain monoamine systems. The ventral tegmental area (VTA), 
basal forebrain, and MFB support intracranial self-stimulation in animal experiments. 
The basal forebrain, nucleus accumbens, olfactory tubercles, frontal cortex, and 
amygdala are all connected to the VTA through dopaminergic projections within the 
MFB. Other neurotransmitters playing a role in these pathways are opioids, GAB A, 
glutamate, and serotonin. 

Interaction with opioid and dopaminergic neurons seems to underlie the reward- 
ing effects of THC (Fig. 12). THC has been shown to stimulate dopaminergic neurons 
from the VTA (73) and to increase the release of dopamine at one of the output, the 
shell of the nucleus accumbens (74). Naloxonazine, a [A, receptor antagonist, reversed 
this effect, suggesting that the increased dopamine release by THC was indirectly 
mediated by an opioid interneuron relieving an inhibitory tone on dopaminergic path- 
ways. Other findings suggesting an opiate mechanism to the reinforcing effects of 
Cannabis include opioid-dependent rats in which rimonabant injection precipitates 
withdrawal (75). Furthermore, cannabinoids can induce the synthesis and release of 
endogenous opioid peptides (76). However, it is important to note that in humans 
naloxone fails to significantly change the subjective and physiological effects of smoked 
marijuana (77). 

Addiction to Cannabis exhibits tolerance and dependence, as proven by the ex- 
istence of a withdrawal syndrome characterized by craving for Cannabis (psychologi- 
cal dependence), decreased appetite, insomnia and nightmares, and some degree of 
agitation, restlessness, or irritability (78). The dependence and withdrawal are not 



/ 14 Raymon and Walls 

REWARD PATHWAY 
Nucleus Accumbens 




THC 



Fig. 12. The reward pathway: possible site of action of Cannabis. A 9 -Tetrahydrocan- 
nabinol may reinforce the effects of opiates and increase the firing of dopamine 
neurons from the ventral tegmental area. Neurons in the dashed line are inhibitory; 
neurons in the solid line are excitatory. 



likely to be severe in the case of THC use because THC is highly lipophilic and slow 
release from the fat tissues in chronic users should result in a tapering of the effects of 
Cannabis over time. Nevertheless, rimonabant can precipitate withdrawal in animals, 
indicating the involvement of CB, receptors in tolerance and dependence to THC (79). 
When agonists are chronically used, receptors desensitize or downregulate. CB, 
receptors are downregulated after chronic exposure to THC (80), and chronic expo- 
sure to an anandamide derivative, methanandamide, causes internalization of G pro- 
tein-linked receptors from the plasma membrane of hippocampal neurons, an effect 
blocked by rimonabant (81 ). These findings would result in an expected reduction of 
effects of cannabinoids when administered chronically. Not all effects of a drug show 
the same degree of tolerance. In animals, tolerance to the hypothermic, locomotor, 
analgesic, and immune-suppressant effects of cannabinoids in mice was studied ( 82, 83 ). 
But there is a notable absence of tolerance to cognition defects induced by THC in 
animals, suggesting that impairing effects of Cannabis on learning and memory would 
persist in chronic marijuana users (84). The same is true of the increased dopamine 
firing in the VTA of rats, suggesting a lack of tolerance to the pleasurable effects of 
Cannabis use in humans (83). 

6. Cannabinoids and Cardiovascular Effects 

Most of the research on cannabinoids has focused on the CNS, yet there are very 
well-described effects of synthetic and endogenous cannabinoids in the periphery, 



Pharmacology of Cannabinoids 



1 15 



Heart 



Reflex 
| MR 



ACh 



NE 




Blood Vessels 



Fig. 13. Control of blood pressure by baroreceptor reflexes: AMetrahydrocannabinol 
causes reflex tachycardia through CB 1 -mediated vasodilatation. ACh, acetylcholine; 
NE, norepinephrine; BP, blood pressure; TPR, total peripheral resistance; HR, heart 
rate; CNS, central nervous system. 



particularly at the level of vascular tone, resulting in complex blood pressure and 
cardiac responses. In humans, the acute administration of cannabinoids causes marked 
tachycardia and a small increase in blood pressure, whereas in chronic users, hypoten- 
sion and bradycardia are generally noted (85,86). Blood vessel tone and heart contrac- 
tility act in concert to regulate blood pressure thanks to what is known as baroreceptor 
reflexes, which involve the autonomic nervous system. Principles of hemodynamics 
illustrate how blood pressure is directly proportional to the total peripheral resistance 
(how constricted blood vessels are) and to the cardiac output (how much blood is 
forced by the pump in the vasculature, the "plumbing"). Cardiac output is itself con- 
trolled by heart rate (how fast the pump is working) and stroke volume (how much 
blood is ejected at each contraction of the heart). 

Total peripheral resistance is the main determinant of blood pressure, and the 
vasculature is mainly under sympathetic innervation control. Any vasoconstriction 
(increased resistance) results in increased blood pressure and the firing of receptors 
situated in the carotid sinuses and the aortic arch. These receptors in turn inform car- 
diovascular centers of the brainstem (in the rostral ventrolateral medulla and the nucleus 
of tractus solitarius), which adapt the autonomic balance between sympathetic and 
parasympathetic outflow to the cardiovascular system in order to restore the blood 
pressure to lower levels (see Fig. 13). The net effect of increased blood pressure is 
increased parasympathetic activity to decrease the heart rate and contractility and 
decreased sympathetic outflow to decrease peripheral resistance of the vasculature. 



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Raymon and Walls 



The effects of cannabinoids could therefore be mediated centrally; CB, receptors are 
found in these cardiovascular centers (87), and intravenous injection of CB, agonists 
decreases sympathetic outflow centrally (probably through presynaptic inhibition), 
leading to vasodilatation and hypotension (88). The responses, being absent in CB, 
knockout mice, suggest that the hypotension and bradycardia resulting from increased 
parasympathetic and decreased sympathetic outflows are CB, mediated (37). These 
effects observed in animals would explain the chronic findings in humans using Can- 
nabis, but not the marked tachycardia associated with acute use of the drug. The marked 
tachycardia would require a decreased parasympathetic and increased sympathetic 
activity, as would occur centrally if inhibition of parasympathetic outflow was occur- 
ring or peripherally if a marked vasodilatation was induced by cannabinoids. Interest- 
ingly, Glass et al. (31) showed a high density of CB, receptors in the dorsal motor 
nucleus of the vagus in the brainstem (parasympathetic centers), and inhibition of this 
center through CB, would result in decreased parasympathetic outflow. It could also 
explain other measured effects of THC in humans besides tachycardia, such as a degree 
of mydriasis and an antiemetic effect. 

To confuse the issue of the cardiovascular effects of cannabinoids further, 
anandamide is a vasodilator in vitro in selective isolated vessel preparations and not 
others, pointing at a direct effect on smooth muscle tone of the vasculature (89). Sub- 
sequent studies have suggested that anandamide acts through inhibition of calcium 
release in smooth muscle cells (90). Recently, anandamide has been implicated as a 
natural ligand of the vanilloid receptor VR, (91 ). VR, receptors are found on sensory 
nerves, and stimulation results in calcium entry and release by the nerve of a number 
of transmitters, which could be associated with vasodilatation, such as nitric oxide, 
substance P, neurokinins, ATP, and calcitonin gene -related peptide. For example, nitric 
oxide diffuses to the smooth muscle and increases cGMP as a mode of vasodilatation, 
and calcitonin gene-related peptide binds to G protein-linked receptors, which increase 
cAMP, another way of causing relaxation of vascular smooth muscle. 

It is important to note that at this point in time, no precise molecular action of 
cannabinoids has been found, and every mechanism proposed has been confirmed and 
refuted by research. Methodology issues, in vitro versus in vivo effects, and species 
differences may be explanatory. Most recently, Offertaler et al. (92) suggested the 
existence of a non-CB,, non-CB 2 , non-VR, endothelial anandamide receptor. This 
receptor would be G protein-coupled and result in MAPK activation. Could the tachy- 
cardia from Cannabis use in humans be simply a result of a direct vasodilatory effect 
resulting in sympathetically mediated baroreceptor reflexes? 

7. Cannabinoids and Immunomodulation 

Immune/inflammatory responses are at the basis of a number of pathological 
conditions. CB, are mainly found centrally and mediate analgesic effects of cannab- 
inoids. CB 2 receptors are mainly found on cells of the immune system, such as mac- 
rophages, T-lymphocytes, and natural killer cells (93). High doses of cannabinoids 
suppress immune responses, whereas low doses cause metabolic stimulation of lym- 
phocytes (94,95). The mechanism of immunomodulation by cannabinoids is still 
unclear, but evidence suggests that CB 2 receptors mediate most of these effects, with 



Pharmacology of Cannabinoids 



downregulation of mast cells and granulocytes and reduced cytokine release, although 
VR[ receptors may be implicated (96). 

The immunomodulatory effects of THC have been tested in a laboratory model 
of multiple sclerosis, experimental autoimmune encephalomyelitis. Placebo-treated 
animals died, whereas THC-treated animals survived and had no or minimal signs 
(97) and notably reduced inflammatory response. These results were reproduced with 
various THC-like drugs, and anecdotal reports from multiple sclerosis patients that 
marijuana would decrease spasticity and symptoms of the disease indicated a possible 
use of Cannabis in the management of this debilitating demyelinating disorder (for a 
review, see ref. 98). However, these effects required high doses of cannabinoids, which 
may not be tolerated in humans or certainly have central effects. Recently, Killestein 
et al. (99) concluded a clinical trial with smaller oral doses of THC and measured 
signs of pro-inflammatory actions in multiple sclerosis patients, which may cause actual 
worsening of the symptoms. More knowledge of CB 2 pharmacology and the develop- 
ment of non-CB, agonists might help in the development of significant anti-inflam- 
matory cannabinoids with therapeutic potential in humans. For example, ajulemic acid, 
a derivative of the main inactive metabolite of THC, carboxy-THC, has promising 
anti-inflammatory action, and a mechanism of action for its effects was recently dis- 
covered ( 100). Ajulemic acid binds peroxisome proliferator-activated receptor gamma 
(PPARy), causing an inhibition of cytokine expression. PPARy is an important tran- 
scription factor, which is also involved in lipid metabolism, glucose homeostasis, and 
adipocyte differentiation (drugs are available interfering with this target in the treat- 
ment of diabetes and hyperlipidemia). Other transcription factors involved in inflam- 
matory/immune responses are targeted by cannabinoids, notably inhibition of activator 
protein- 1, nuclear factor kB, and signal transducer and activator of transcription ( 101- 
103). These data point to a mechanism involving changes in gene expression, prob- 
ably mediated through complex signal transduction changes, which may or may not 
involve classic cannabinoid receptors on the surface of the cell because cannabinoids 
are lipophilic and may access transcription factors intracellularly. 

8. Conclusions 

The complex pharmacology of cannabinoids, whether exogenous or endogenous, 
exists only in its infancy. From the discovery of specific cannabinoid receptors and 
other targets to that of endogenous ligands and a biochemical pathway of synthesis, 
degradation and reuptake, the therapeutic potential of cannabinoids is only emerging. 
Central actions on motor regulatory pathway may give rise to drugs useful in dyskinesias 
such as Huntington's or Parkinson's disease. Central effects on glutamate release may 
yield medications aimed at decreasing the pathological consequences of strokes. The 
analgesic effects of cannabinoids already see some application in neuropathic pain 
(104). Could an antagonist help in increasing memory in Alzheimer's disease patients? 
Already, central effects such as appetite stimulation and antiemetic properties are clini- 
cally used. Peripheral effects on the cardiovascular system could help in the develop- 
ment of novel antihypertensive medications. The peripheral pharmacology of 
cannabinoids may also lead to drugs modifying immune or inflammatory function, 
such as multiple sclerosis, as well as asthma or autoimmune disorders. The future will 



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shed light on the place of cannabinoid pharmacology in our medical arsenal to fight 
diseases, and developing research will undoubtedly enhance our understanding of 
existing and yet unknown molecular pathways cells use to appropriately respond to 
internal and external stimuli. 



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Chapter 6 



The Endocannabinoid System 
and the Therapeutic Potential 
of Cannabinoids 

Billy R. Martin 

1. Introduction 

Much has been written about the history of the medical uses of cannabis (1 ). In 
the past two centuries, there have been numerous references to the use of cannabis 
extracts for a wide range of disorders (2). In the early part of the 20th century, a 
standardized cannabis elixir was marketed in the United States. Following the intro- 
duction of synthetic drugs such as barbiturates and opioids into medicine, interest in 
cannabis elixir declined. The discovery of the primary active constitutent in mari- 
juana, A 9 -tetrahydrocannabinol (THC), in 1964 (3) rekindled interest in the area. How- 
ever, the emphasis shifted to synthetic cannabinoids rather than the plant or plant 
extracts. For example, in the 1970s, clinical studies were conducted in an effort to 
determine the efficacy of THC as an analgesic (4), antiemetic (5), antidepressant (6,7), 
appetite stimulant (7), and for treatment of glaucoma (8). These efforts resulted in the 
approval of THC (dronabinol, Marinol™) for treatment of chemotherapy-induced nau- 
sea and vomiting in 1985 and for appetite stimulation in 1992. 

There have been several attempts to develop THC derivatives for medical uses. 
Nabilone was found to have anxiolytic (9) and antiemetic properties (10) and is pres- 
ently marketed as Cesamet™. Levonantradol was evaluated as an antiemetic (11) and 
analgesic (12) but was never approved for clinical use. Nabitan was studied clinically 
as an analgesic in cancer pain (13) but, like levonantradol, was never approved for 
use. However, the emphasis shifted back to cannabis in the early 1990s following the 
HIV epidemic. The lack of effective treatments for HIV led the advocacy community 

From: Forensic Science and Medicine: Marijuana and the Cannabinoids 
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey 



725 



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Martin 



to demand more effective treatments and greater access to any material that might be 
beneficial for symptoms management. Hence, there has been increased attention to 
smoked marijuana not only for HIV patients, but also for a wide range of diseases. 
During this same period it became obvious that THC and marijuana were producing 
their effects through a newly discovered endocannabinoid system. The discovery of 
this biological system has provided opportunities for developing new medications that 
were not possible previously. 

2. Endocannabinoid System 

Although early structure-activity relationship (14) and initial receptor-binding 
studies (15) suggested the existence of cannabinoid receptors, it was not until the late 
1980s that compelling evidence for a cannabinoid receptor emerged. Devane et al. 
( 16) characterized a binding site that had all of the properties of a cannabinoid recep- 
tor. Shortly thereafter, the cannabinoid receptor was cloned, thereby verifying the 
existence of a specific target for cannabinoids (17). Compton et al. (18) extended 
these characterizations by showing a strong correlation between binding affinity for 
this site and cannabinoid potency for a large number of cannabinoid analogs. This 
receptor is referred to as the CB, cannabinoid receptor. The cannabinoid receptor, 
while uniquely recognized by cannabinoids, is a member of a large family of receptors 
that are coupled to G proteins. CB, receptors are also found in brain and peripheral 
tissues that include sensory nerve fibers, the autonomic nervous system, testis, and 
immune cells ( 19). Surprisingly, the CB, cannabinoid receptor was found to be present 
in very high quantities in the central nervous system, exceeding the levels of almost 
all neurotransmitter receptors. Although the CB, receptor is present throughout brain, 
the highest levels are found in brain structures associated with neurophysiological 
functions altered by cannabinoids (20). The densest binding occurs in the basal gan- 
glia (substantia nigra pars reticulata, globus pallidus, entropeduncular nucleus, and 
lateral caudate putamen) and the molecular layer of the cerebellum. Receptors in these 
regions are consistent with cannabinoid interference with movement. Intermediate levels 
of receptor binding are present in the CA pyramidal cell layers of the hippocampus, 
the dentate gryus, and layers I and VI of the cortex. The presence of CB, receptors in 
these regions is expected given the effects of cannabinoids on cognitive processes. 
The hippocampus stores memory and codes sensory information. The presence of can- 
nabinoid receptors in regions associated with mediating brain reward (ventromedial 
striatum and nucleus accumbens) is consistent with the role that cannabinoids play in 
the neurobiology of reward (21 ). Lower levels are found in the brainstem, hypothala- 
mus, corpus callosum, and the deep cerebellum nuclei. At the cellular level, the CB, 
receptors are located predominantly on presynaptic terminals of y-aminobutyric acid 
(GABA) and glutamate neurons. In the striatum they are present on glutamatergic 
terminals emanating from the cortex (22), GABA interneurons (23), and axon termi- 
nals of GABA-associated medium spiny neurons (24). Cerebellar CB, receptors are 
present on excitatory terminals and GABA interneurons (25). 

A second receptor subtype has been identified and is termed the CB 2 cannab- 
inoid receptor (26). The CB 2 receptor is present primarily in tissues that are associated 



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with immune function, including spleen, thymus, tonsils, bone marrow, pancreas, 
splenic macrophages/monocytes, mast cells, and peripheral blood leukocytes (19). The 
messenger RNA for the CB 2 receptor varies considerably among various human blood 
cell populations, with B -lymphocytes > natural killer cells » monocytes > polymor- 
phonuclear neutrophils > T8 -lymphocytes > T4-lymphocytes (27). There is no evi- 
dence that this receptor subtype is associated with neuronal tissue. However, there is 
evidence that CB 2 receptors can be induced in microglia, a cell of macrophage lineage 
that is present in brain (28). CB[ and CB 2 receptors are activated by THC. 

Several cannabinoid receptor signaling pathways have also been identified. Both 
cannabinoid receptor subtypes have the molecular signature of G protein-coupled 
receptors. Actually, evidence for a G protein-coupled cannabinoid receptor preceded 
the cloning of the CB, receptor (29). There is strong evidence for CB, receptor cou- 
pling to multiple G i/0 proteins (30). The predominant effects of cannabinoids occur 
through inhibitory G protein function, including inhibition of adenylyl cylase, inhibi- 
tion of calcium channels (N and Q types), as well as activation of inwardly rectifying 
potassium channels (31,32). These actions are highly relevant to neurotransmitter 
release, as will be discussed later. 

Although evidence of cannabinoid receptors and their signaling pathways was 
sufficient to establish biological relevance, identification of the natural ligands was 
essential for functional relevance. Three distinct arachidonoyl derivatives have been 
identified as natural ligands for the cannabinoid receptors. The amide anandamide 
(33), the ester 2-arachidonoyl-glycerol (34,35), and the 2-arachidonoyl glyceryl ether 
(36) have been identified thus far as endocannabinoids. These endogenous substances 
are considered endocannabinoids because they activate CB , cannabinoid receptors and 
produce effects that are consistent with CB, cannabinoid receptor activation. More- 
over, the synthetic and degradative pathways for anandamide and 2- 
arachidonoylglycerol have been identified in relevant tissues. 

There is substantial evidence that a calcium-dependent, energy-independent 
transacylase transfers arachidonic acid from the sn-l position of phosphatidylcholine 
to the amino group in phosphatidylethanolamine to form Af-arachidonoyl-phosphati- 
dylethanolamine, with subsequent hydrolysis by a phospholipase D-type enzyme to 
form anandamide (37). Inactivation of anandamide occurs primarily via fatty acid 
amide hydrolase, an enzyme that has been cloned (38). Blockade or deletion of this 
enzyme in mice greatly potentiates the actions of exogenously administered anandamide 
(39). Diacylglycerol lipase synthesizes 2-arachidonoylglycerol (40). This enzyme is 
required for axonal growth during development and for retrograde synaptic signaling 
at mature synapses. The inactivation of 2-arachidonoylglycerol occurs by a 
monoglyceride lipase (41). Both of these synthetic and degradative 2- 
arachidonoylglycerol enzymes have been cloned. 

The discovery that the endogenous cannabinoid system consists of two receptor 
subtypes, signaling pathways, endogenous ligands, and synthetic and metabolic path- 
ways for these ligands provided unique opportunities to understand the mechanisms 
through which cannabinoids produce their effects. More importantly, the endogenous 
cannabinoid system provides a means for verifying whether cannabinoids are acting 
directly or indirectly to produce their wide range of pharmacological effects. At the 



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same time, the functional role of the endogenous cannabinoid system in normal physi- 
ological processes, as well as in disease states, is beginning to emerge. This chapter is 
confined to appetite, emesis, pain, and drug dependence. 

3. Appetite 

The desire to consume food represents one of the fundamental physiological pro- 
cesses essential for survival. It is therefore not surprising that appetite is regulated by 
a highly complex integration of hormonal and neuronal systems to maintain homeo- 
stasis. Disruptions of these homeostatic mechanisms can result in either food depriva- 
tion or excess eating. Appetite is also easily disrupted in many disease states, such as 
cancer and HIV infection. 

There is ample evidence that the endogenous cannabinoid system plays a role in 
appetite homeostasis. Although both marijuana and THC have been shown to stimu- 
late appetite, direct evidence for the involvement of cannabinoid receptors was pro- 
vided by a study in which CB, receptor knockout mice ate less than wild-type mice 
following food restriction (42). The selective antagonist, rimonabant (SR 141716), 
provided additional support for CB , receptor involvement in that this compound reduced 
food intake in wild-type but not CB! knockout mice (42). There are several lines of 
evidence indicating that the brain is a prominent site for cannabinoid regulation of 
appetite. For example, the hypothalamus contains both CB, receptors and the 
endocannabinoids anandamide and 2-arachidonoylglycerol. Direct injections of 
anandamide into the hypothalamus of rats induced hyperphagia, an effect that was 
blocked by the CB, receptor antagonist rimonabant (43). In addition, there is evidence 
of an interrelationship between the endocannabinoids and leptin, a key anorexigenic 
agent that is secreted by adipose tissue and acts within the hypothalamus at the arcuate 
nucleus to suppress appetite-stimulating peptides and stimulate the activity of appe- 
tite-reducing peptides. Di Marzo et al. (42) demonstrated that acute treatment with 
leptin reduces the levels of anandamide and 2-arachidonoyl glycerol in the hypothala- 
mus of normal rats. On the other hand, these endocannabinoids were elevated in obese 
leptin-deficient ob/ob and obese leptin-receptor-deficient db/db mice. 

A second central component of cannabinoid-mediated food intake likely involves 
reward pathways and the hedonic aspect of eating. Higgs et al. (44) recently demon- 
strated that both THC and anandamide increased sucrose intake in rats, whereas 
rimonabant decreased it. Fasting increases levels of anadamide and 2- 
arachidonoylglycerol in the nucleus accumbens, a brain structure crucial for reward 
(45). Levels of endocannabinoids were not changed in satiated rats. In diet-induced 
obese rats there was a significant decrease in CB, receptor density in hippocampus, 
cortex, nucleus accumbens, and entopeduncular nucleus, but not in hypothalamus (46). 
Collectively, these data strongly implicate a central mechanism for endocannabinoid 
influence on diet. 

There are also several suggestions that endocannabinoids act peripherally to regu- 
late metabolism. Cota et al. (47) found CB, receptors in adipocytes, thereby raising 
the possibility of a direct peripheral lipogenic mechanism. Furthermore, rimonabant 
stimulated Acrp30 (adiponectin) messenger RNA expression in adipose tissue and 
reduced hyperinsulinemia in obese (fa/fa) rats (48). At present, there is no evidence 



Therapeutic Potential of Cannabinoids 



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that CB, receptor agonists produce opposing effects. Nevertheless, these findings sug- 
gest that the endocannabinoid system may have a direct effect on energy balance and 
lipid metabolism. 

Based on the above findings, it seems logical that the endocannabinoid system 
could be manipulated for the purpose of treating either weight loss or obesity (49). 
Indeed, one of the most consistent effects of smoking marijuana is an increase in 
appetite. A recent study compared marijuana smoking with oral THC, and both treat- 
ments increased food intake (50). However, the results in patient populations have 
been less definitive. Beal et al. (51) examined the effects of THC on appetite and 
weight in patients with AIDS -related anorexia. They reported modest improvement in 
appetite and mood along with stabilization in weight. Several early investigations 
showed that THC increased appetite in cancer patients (52,53). More recently, Jatoi et 
al. (54) compared megestrol acetate with THC for palliating cancer-associated anor- 
exia. They found that megestrol acetate provided superior anorexia palliation among 
advance cancer patients. On the other hand, Nelson et al. (55) evaluated the effects of 
THC on appetite in advanced cancer patients suffering from anorexia. Most patients 
completed the 28-day study and experienced improved appetite. With regard to the 
CB, receptor antagonist rimonabant, it has been shown to be effective in reducing 
food intake in both laboratory animals (described earlier) and in promoting weight 
loss in humans during recent phase III clinical trials. 

4. Emesis 

Although emesis has a dramatic impact on appetite, the mechanisms underlying 
emesis trials and nausea/vomiting are quite distinct. In contrast to the predominant 
role of the hypothalamus in appetite, the postrema-nucleus tractus solatarius in the 
brainstem plays an essential role in emesis. Additionally, the dopaminergic, cholin- 
ergic, and serotonergic systems in the gastrointestinal tract can contribute to emesis. 
Several animal studies indicate a direct role for endocannabinoid modulation of eme- 
sis. Darmani et al. (56) showed that CB, receptor agonists reduced cisplatin-induced 
emesis in the least shrew, whereas the antagonist rimonabant produced the opposite 
effects. Similar findings were reported with cannabinoid agonists that attenuated 
lithium-induced vomiting in the musk shrew (57,58). In addition, combinations of 
inactive doses of THC and ondansetron were effective in blocking vomiting in the 
musk shrew (58). The musk shrew has also been used to study conditioned retching, 
an animal model of anticipatory nausea and vomiting. THC completely suppressed 
conditioned retching in this model (59). In addition, cannabinoid agonists suppressed 
lithium-induced conditioned rejection, a model of nausea in rats (60). Opioids are 
known to be powerful emetogenic agents. Activation of the cannabinoid system was 
also effective in blocking opioid-induced vomiting in ferrets (61). CB, cannabinoid 
receptors were strongly implicated in that rimonabant blocked the action of cannab- 
inoid agonists in this model. Importantly, Darmani et al. (62) found prominent CB, 
receptor binding in the nucleus tractus solartius of the shrew. The exact nature of the 
role played by endocannabinoids is unclear at this time. A metabolically stable analog 
of anandamide blocked vomiting, whereas another endocannabinoid, 2- 
arachidonoylglycerol, was emetogenic (62). 



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As for clinical evidence, anecdotal reports of patients smoking marijuana to con- 
trol chemotherapy-induced nausea and vomiting provided the initial clues. These reports 
led to clinical studies with THC in which it was found to be useful in patients whose 
chemotherapy-induced nausea and vomiting were refractory to other standard 
antiemetics available at that time (63). Plasse et al. (53) reported that combinations of 
THC and prochlorperazine resulted in enhancement of efficacy as measured by dura- 
tion of episodes of nausea and vomiting and by severity of nausea. In addition, the 
incidence of psychotropic effects from THC appeared to be decreased by concomitant 
administration of prochlorperazine. The combination was significantly more effective 
than was either single agent in controlling chemotherapy-induced nausea and vomit- 
ing (64). Nabilone, a synthetic derivative of THC, was also reported to be an effective 
oral antiemetic drug for moderately toxic chemotherapy (65). Cannabinoids have also 
been found to be effective in treating nausea and vomiting in children undergoing 
chemotherapy ( 66,67). As for the current status of antiemetics, serotonergic anatagonists 
such as ondansetron have become the standards for managing emesis. These agents 
have proven to be effective in preventing chemotherapy-induced nausea and vomiting 
in most patients. However, delayed nausea and vomiting are less well controlled. There- 
fore, the search for more effective agents continues. Combination therapy with 
ondansetron and THC has not been fully explored. In addition, there is a need for a 
higher-efficacy CB, receptor agonist with fewer side effects. 

5. Pain 

Animal studies have firmly established cannabinoid-induced analgesia in a wide 
array of acute and chronic pain models (68). Most of this evidence is based on CB, 
receptor agonists such as THC and related synthetic derivatives. It has been firmly 
established that these effects are being mediated through the endocannabinoid system. 
First, there is an excellent correlation between cannabinoid analgesics and their affin- 
ity for the CB, receptor (69). Second, the CB, receptor antagonist rimonabant is effec- 
tive in blocking the analgesic effects of cannabinoid agonists (70,71). As expected, 
the endogenous ligands anandamide and 2-arachidonoylglycerol exhibit analgesic prop- 
erties when administered to laboratory animals (34,72). Mice with genetic deletion of 
fatty acid amidohydrolase, the enzyme that hydrolyzes anandamide, exhibit enhanced 
analgesic activity with exogenously administered anandamide (39). More importantly, 
these animals have elevated endogenous anandamide levels as well as an increased 
pain threshold, evidence that supports a physiological role for endocannabinoids in 
pain perception. Additional evidence for endocannabinoid pain modulation includes 
cannabinoid suppression of spinal and thalamic nociceptive neurons, identification of 
spinal, supraspinal, and peripheral sites of action, as well as evidence that 
endocannabinoids are released upon electrical stimulation of the periaqueductal gray 
and following inflammation in the periphery (73,74). 

Although nociceptive events will stimulate the release of endocannabinoids, the 
exact nature of their actions on pain neurotransmission remains to be fully established. 
CB, receptors are located predominantly on presynaptic terminals, and their activa- 
tion results in the inhibition of the neurotransmitter released at this site. Hohman et al. 



Therapeutic Potential of Cannabinoids 



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examined the distribution of CB, receptors in rat dorsal root ganglion and found them 
present in only a subset of neurons containing substance P and calcitonin gene-related 
peptide (75). There is evidence for localization of CB, receptors on neurons contain- 
ing endogenous opioids. Welch and Stevens (76) demonstrated that cannabinoid ago- 
nists potentiated morphine analgesia in laboratory animals. This laboratory later 
demonstrated that THC, but not anandamide, stimulates the release of dynorphin A 
(77). While there is an abundance of data illustrating interactions between the opioid 
and cannabinoid systems, the exact nature of these interactions remains to be eluci- 
dated. 

Although there is strong evidence that the endocannabinoid system regulates 
pain pathways, the effectiveness of CB, agonists as analgesics has been equivocal. 
Despite intense efforts to develop cannabinoid analgesics, there has been little success 
in devising a CB, receptor agonist that is devoid of behavioral effects. For example, 
Noyes et al. (78) found that oral THC was as efficacious as codeine in producing 
analgesia in a patient population, but its behavioral side effects precluded the use of 
higher doses. As for synthetic cannabinoid derivatives that might be useful as analge- 
sics, nabitan is one such analog that was evaluated in at least two studies. Jochimsen et 
al. (79) failed to observe pain relief in cancer patients, and there was some evidence 
for increased pain sensitivity. On the other hand, another research group (13) reported 
analgesia comparable to that of codeine in cancer patients. Levonantradol, another 
cannabinoid derivative, elicited some benefit for postoperative surgical pain but only 
at doses that produced significant behavioral disturbances (80). Several recent clinical 
studies have found THC to lack sufficient efficacy in postoperative pain (81), neuro- 
pathic pain (82), and refractory neuropathic pain (83). On the other hand, THC was 
found to exert some benefit in treating intractable neuropathic pain in two adolescents 
(84). A review of clinical studies regarding cannabinoid agonist treatment of cancer 
pain led the author to conclude that the present studies do not justify the use of can- 
nabinoid agonists for pain management (85). 

The evidence suggests that the CB , receptor agonists that have been developed 
thus far are unlikely to be highly efficacious in controlling high-intensity pain. How- 
ever, the possibility remains that they might be useful in more moderate pain, particu- 
larly in case in which some of the typical cannabinoid side effects (sedation, dizziness, 
etc.) might be more tolerated. Theoretically, CB, receptor agonists should be effective 
as adjuvants to other analgesics. Numerous preclinical studies have shown that THC 
will enhance opioid analgesia. However, in a recent study in human experimental pain 
models, THC offered relatively small additive analgesic effects when combined with 
morphine (86). It remains to be determined whether similar results would occur in 
pain patients. 

There are several possible explanations for the discrepancy between the analge- 
sic effects of CB, receptor agonists in laboratory animals and humans. Certainly, higher 
doses can be administered to laboratory animals, and hence greater analgesic effects 
achieved, than in humans. Pharmacokinetics may also play a very important part. The 
studies that have been carried out thus far have relied on oral administration of THC, 
a route that does not allow for easy optimization of treatment. Efforts are underway to 
develop alternative formulations of THC to allow for other routes of administration. 



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Rectal suppositories of THC hemisuccinate have been found to be effective in treating 
spasticity and pain (87). A water-soluble analog of THC has been developed that may 
be appropriate for intravenous use (88). There have been recent studies demonstrating 
that topical administration of cannabinoids produce analgesic effects (89). Moreover, 
topical administration produced a synergistic interaction with spinally administered 
cannabinoids. A separate group of investigators reported an analgesic interaction 
between topical opioids and cannabinoids administered either topically or spinally 
(90). These observations reinforce the notion that treatment regimens of opioid and 
cannabinoids combinations have yet to be optimized clinically. Unfortunately, a topical 
preparation of THC or related cannabinoid is not yet available for clinical use. Another 
attractive approach is the inhalation route. An inhalation formulation of THC was devel- 
oped years ago, but unfortunately it produced bronchial irritation (91). The recent develop 
of a THC aerosol delivered through a metered-dose inhaler holds promise (92). 

The discussion so far has been devoted to nonselective CB, and CB 2 agonists, 
such as THC, because most of the analgesic literature has been generated with these 
compounds. The discovery of the CB 2 receptor in nonneuronal tissues such as immune 
cells attracted interest in its potential modulation of immune function. However, there 
are now numerous reports that CB 2 selective agonists have analgesic properties. One 
such CB 2 selective agonist is AM 1241, which was shown to be highly active in a 
thermal pain model in rats (93). It was also shown to suppress capsaicin-induced 
hyperalgesia (94). HU 308 is another CB 2 selective agonist that has been reported to 
produce analgesic effects in rodents (95). The advantage of these compounds is that 
they are devoid of the behavioral effects produced by CB, selective agonists. At present 
there are no reports of clinical efficacy of CB 2 selective agonists. 

6. Drug Dependence 

Marijuana dependence has long been a controversial issue, in part as a result of 
the lack of understanding of drug dependence. It is clear that a major physical with- 
drawal syndrome does not occur upon abrupt cessation of marijuana use. Certainly, 
dependence on many substances occurs without a prominent physical aspect of the 
syndrome. What is clear is that continual use of marijuana can lead to dependence as 
defined by the Diagnostic and Statistical Manual of Mental Disorders, 4th ed. crite- 
ria, or essentially the inability to the user to exert control over their use. In actual fact, 
an abrupt cannabinoid withdrawal syndrome was described in humans following dis- 
continuation of a rather rigorous treatment regimen of THC (96,97). Studies in more 
recent times have used treatment regimens that more closely reflect typical marijuana 
use patterns and have also demonstrated an abstinence symptom that included subjec- 
tive effects of anxiety, irritability, and stomach pain, as well as decreases in food 
intake, following abrupt withdrawal from continued administration of either oral THC 
(98) or marijuana smoke inhalation (99). There have been several efforts to devise 
strategies for treating marijuana dependence. Haney et al. (100) found that bupropion 
worsened mood during marijuana withdrawal. The antidepressant nefazodone pro- 
vided partial relief ( 101 ). They also demonstrated that oral THC decreased marijuana 
craving and withdrawal signs during abstinence (102). 



Therapeutic Potential of Cannabinoids 



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Demonstrating a well-defined abstinence withdrawal syndrome following pro- 
longed cannabinoid administration in laboratory animals also presented challenges. 
Several unconditional behavioral effects, including hyperirritability, tremors, and an- 
orexia, were reported to occur during THC abstinence ( 103), while other studies failed 
to observe abrupt withdrawal effects following chronic THC administration in dogs 
(104) or rats (105,106). Abrupt withdrawal from chronic THC has been reported in 
rhesus monkeys (107). The fact that readministration of THC reversed the withdrawal 
effects suggested that the animals were cannabinoid-dependent. The development of 
rimonabant (70), a selective CB, receptor cannabinoid antagonist, represented the first 
opportunity to determine whether a physical withdrawal syndrome could be precipi- 
tated with an antagonist challenge. Antagonist-precipitated withdrawal is much easier 
and more reliable to quantitate than withdrawal following abrupt cessation of the de- 
pendence-producing drug. Indeed, a robust withdrawal syndrome was observed in THC- 
treated rats that were challenged with rimonabant ( 108,109). Subsequent studies verified 
precipitated withdrawal in both mice (110) and dogs (111). Another contribution of 
rimonabant was that it enabled investigators to carefully document the symptoms of 
withdrawal as well as the time course, both of which are critical for assessing abrupt 
withdrawal. Subsequently, Aceto et al. (112) were able to document abrupt withdrawal 
following cessation of infusion with the synthetic CB, receptor agonist WIN 55,212. 

Although it was important to demonstrate that abrupt and precipitated withdrawal 
can be documented, most dependence-producing agents will also be self-administered 
by laboratory animals. Unfortunately, THC is not readily self-administered by ani- 
mals. There was an early report that rats would self-administer THC ( 113). However, 
it has not been an easy task to get rats to self-administer cannabinoids (114). It has 
now been shown that THC can be reliably self-administered in squirrel monkeys 
(115,116). 

There is now increasing knowledge that the endocannabinoid system participates 
in dependence on drugs other than THC. There has always been considerable interest 
in the interactions of cannabinoids and opioids as it relates to dependence. Naloxone 
has been reported to precipitate withdrawal effects in rats treated chronically with 
THC (117,118). Conversely, naloxone was ineffective in precipitating withdrawal in 
THC-dependent monkeys ( 107), pigeons ( 104), or mice (119). It has long been known 
that THC produces a moderate attenuation of naloxone-precipitated withdrawal in 
morphine-dependent mice (120,121 ) and rats (122,123). The endogenous cannabinoids 
anandamide (124) and 2-arachidonoylglycerol ( 125 ) have both been reported to decrease 
naloxone-induced morphine withdrawal. 

Actually, the availability of mice lacking either ti-opioid or CB, receptors has 
greatly advanced our understanding of the interrelationship between the opioid and 
endocannabinoid systems. CB , receptor knockout mice exhibited substantial decreases 
in both morphine self-administration and naloxone-precipitated morphine withdrawal 
(126). In addition, rimonabant reduced the rewarding responses of morphine in the 
conditioned place preference paradigm (127). Co-administration of rimonabant and 
morphine led to decreases in naloxone-precipitated wet dog shakes and jumping but 
had no effects on other indices of opioid withdrawal, including paw tremors, ptosis, 
sniffing, and body tremors (127). Repeated administration of rimonabant in rats 



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implanted with morphine pellets reduced some, but not all, naloxone precipitated with- 
drawal effects (128). 

The converse also appears to be true, in that opioid receptors may play a modu- 
latory role on cannabinoid dependence. Rimonabant-precipitated THC withdrawal 
symptoms were significantly diminished in pre-proenkephalin-deficient mice com- 
pared to the wild-type mice (129). Similarly, mice lacking the ix-opioid receptor 
exhibited significant attenuation of rimonabant-precipitated withdrawal signs com- 
pared with the wild-type controls. These findings implicate a role for opioid system in 
the modulation of cannabinoid dependence. 

The finding that modulation of the endocannabinoid system is capable of influ- 
encing opioid dependence — and vice versa — raises the possibility that the CB, recep- 
tor antagonist might influence opioid dependence. Indeed, Navarro et al. ( 130) found 
that rimonabant was capable of blocking heroin self-administration in rats. Several 
other laboratories evaluated CB , receptor agonists and antagonists for their ability to 
influence reinstatement of heroin self-administration ( 131,132). They found that sev- 
eral CB, receptor agonists restored heroin-seeking behavior, whereas rimonabant pre- 
vented reinstatement. 

The question arises as to whether the endocannabinoid system is involved in 
dependence to drugs other than opioids. De Vries et al. (133) reported that the potent 
CB , receptor agonist HU210 provoked relapse to cocaine seeking after prolonged with- 
drawal periods. In addition, rimonabant attenuated relapse induced by re-exposure to 
cocaine-associated cues or cocaine itself, but not relapse induced by exposure to stress. 
On the other hand, another laboratory reported that a CB, receptor agonist attenuated 
the effects of cocaine on brain self-stimulation thresholds, whereas rimonabant did 
not alter cocaine's effects (134). These findings suggest that the endocannabinoid sys- 
tem plays a greater role in relapse to cocaine use than in maintaining cocaine self- 
administration. 

Another drug that is frequently used in conjunction with marijuana is alcohol. 
There are several indications that the endocannabinoid system may influence alcohol 
intake. It has been shown that rimonabant will decrease alcohol self-administration in 
laboratory animals ( 135) and that alcohol preference is reduced by rimonabant ( 136). 
Also, alcohol withdrawal symptoms are absent in CB, receptor knockout mice, which 
provides further support for a role of the endocannabinoid system in alcohol depen- 
dence. Rimonabant has also been evaluated for its potential effects on the motiva- 
tional effects of nicotine in the rat (137). Rimonabant decreased nicotine 
self-administration but did not substitute for nicotine nor antagonize the nicotine cue 
in a nicotine-discrimination procedure. It also blocked nicotine-induced dopamine 
release in the shell of the nucleus accumbens and the bed nucleus of the stria terminalis 
(137). Dopamine release induced by ethanol in the nucleus accumbens was also re- 
duced by rimonabant. 

The fact that the endocannabinoid system is an active participant in the depen- 
dence on a wide range of drugs argues that it may play a fundamental role in the 
perturbation of reward pathways that underlie drug dependence. These results suggest 
that activation of the endogenous cannabinoid system may participate in the motiva- 
tional and dopamine-releasing effects of nicotine and ethanol as well as possibly other 



Therapeutic Potential of Cannabinoids 



135 



drugs of abuse. Thus, CB, receptor antagonists may be effective in treating drug 
dependence induced by opioids, psychomotor stimulants, nicotine, and ethanol, in 
addition to marijuana. 

7. Summary 

Because the endocannabinoid system represents an important target for address- 
ing symptoms arising from numerous disease states, the ability to manipulate this 
system becomes of paramount importance. At present, the only means of activating 
the endocannabinoid system is with CB, and CB 2 receptor agonists. The disadvantage 
of CB, receptor agonists is that they have a broad pharmacological spectrum of action 
that limits their clinical utility. Attempts to develop CB, receptor agonists that have 
improved the therapeutic-to-adverse effect ratio have met with limited success. How- 
ever, the new evidence that is emerging regarding the multiple signaling pathways 
activated by the CB , receptor provides encouragement that development of agonists 
with improved pharmacological profile is possible. Moreover, structure-activity rela- 
tionship studies continually provide new chemical templates for agents that activate 
the CB , receptor. In the near term, the most likely success will come from new formu- 
lations of current CB, receptor agonists that are already approved for clinical use. 

As for selective CB 2 receptor agonists, there is intense interest in these com- 
pounds as potential therapeutic agents because they will be devoid of the behavioral 
effects that currently plague the CB, receptor agonists. The fact that selective CB 2 
receptor agonists have been found to be effective in some animal models of pain pro- 
vides an exciting possibility for development of new analgesics. 

Efforts are also underway to develop inhibitors of the enzymes that degrade 
anandamide. Indeed, deletion of this enzyme in mice through genetic engineering re- 
sulted in elevated anandamide levels and increased resistance to pain (39). Highly 
potent inhibitors of this enzyme have also been synthesized (138). By elevating 
anandamide levels, these inhibitors represent an entirely new strategy for activating 
the endocannabinoid system. Elevation of 2-arachidonoylglycerol levels could occur 
through the blockade of monoglyceride lipase, the enzyme that metabolizes this 
endocannabinoid (41). There are at present no selective inhibitors of this enzyme. 

It is also abundantly clear that attenuating the endocannabinoid system has im- 
portant therapeutic uses. The CB, receptor antagonist rimonabant has been shown to 
be effective in both animal models and clinical trials for treatment of decreased appe- 
tite and increased weight loss. Moreover, it has been shown to alter alcohol, cocaine, 
heroin, and nicotine dependence. Another potential means of attenuating the 
endocannabinoid system is through inhibition of the synthesis of anandamide and 2- 
arachidonolyglycerol. Although these enzymes have been identified, there are at present 
no inhibitors shown to have potential as therapeutic agents in, for example, obesity or 
drug dependence. 

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cipitated withdrawal signs in mice chronically treated with morphine. Neuropharmacol- 
ogy 34, 665-668. 

125. Yamaguchi, T., Hagiwara, Y., Tanaka, H., et al. (2001) Endogenous cannabinoid, 2- 
arachidonoylglycerol, attenuates naloxone-precipitated withdrawal signs in morphine- 
dependent mice. Brain Res. 909, 121-126. 

126. Ledent, C., Valverdej, O., Cossu, G., et al. (1999) Unresponsiveness to cannabinoids and 
reduced addictive effects of opiates in CB1 receptor knockout mice. Science 283, 401- 
404. 

127. Mas-Nieto, M., Pommier, B., Tzavara, E. T., et al. (2001) Reduction of opioid depen- 
dence by the CB(1) antagonist SR141716A in mice: evaluation of the interest in pharma- 
cotherapy of opioid addiction. Br. J. Pharmacol. 132, 1809-1816. 

128. Rubino, T., Massi, P., Vigano, D., Fuzio, D., and Parolaro, D. (2000) Long-term treat- 
ment with SR141716A, the CB1 receptor antagonist, influences morphine withdrawal 
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129. Valverde, O., Maldonado, R., Valjent, E., Zimmer, A. M., and Zimmer, A. (2000) Can- 
nabinoid withdrawal syndrome is reduced in pre-proenkephalin knock-out mice. J. 
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130. Navarro, M., Carrera, M. R. A., Fratta, W., et al. (2001) Functional interaction between 
opioid and cannabinoid receptors in drug self-administration. /. Neurosci. 21, 5344-5350. 

131. Fattore, L., Spano, M. S., Cossu, G., Deiana, S., and Fratta, W. (2003) Cannabinoid 
mechanism in reinstatement of heroin-seeking after a long period of abstinence in rats. 
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132. De Vries, T. J., Homberg, J. R., Binnekade, R., Raaso, H., and Schoffelmeer, A. N. M. 
(2003) Cannabinoid modulation of the reinforcing and motivational properties of heroin 
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134. Vlachou, S., Nomikos, G. G., and Panagis, G. (2003) WIN 55,212-2 decreases the rein- 
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135. Freedland, C. S., Sharpe, A. L., Samson, H. H., and Porrino, L. J. (2001) Effects of 
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282. 

136. Wang, L., Lui, J., Harvey- White, J., Zimmer, A., and Kunos, G. (2003) Endocannabinoid 
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137. Cohen, C, Perrault, G., Voltz, C, Steinberg, R., and Soubrie, P. (2002) SR141716, a 
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and anandamide. Proc. Natl. Acad. Sci. USA 97, 5044-5049. 



Chapter 7 



Immunoassays for the Detection 
of Cannabis Abuse 

Technologies, Development Strategies, 
and Multilevel Applications 

Jane S-C. Tsai 

1. Introduction 

The power of molecular recognition and effective interaction of specific binding 
partners have been exploited to develop assay technologies for diverse biochemical 
analysis. The unique features of immunoglobulins and technological advancement in 
antibody engineering and manipulation have made antibodies the most versatile bind- 
ing reagents for detecting analytes of interest in a variety of matrices. The term immuno- 
assay is customarily used to denote antibody-mediated analytical procedures; however, 
there are assortments of nomenclature for various immunoassay techniques that usu- 
ally are named after the reaction principle of the particular immunoassay format. 

A number of immunoassay technologies have been applied to the development 
of assays for small molecules such as drug compounds and their metabolites. To date, 
these immunoassays have been widely utilized as cost-effective initial tests to effi- 
ciently screen out the negative specimens from further analysis in the two-stage drugs- 
of-abuse testing (DAT) programs. Subsequently, the non-negative or presumptive positive 
specimens are subjected to confirmatory testing with an alternative chemical principle 
such as gas (or liquid) chromatography/mass spectrometry (GC/MS or LC/MS). 

Proper utilization of DAT technologies requires familiarity with the characteris- 
tics of the analytical methodologies employed. Each of the abused drugs has specific 

From: Forensic Science and Medicine: Marijuana and the Cannabinoids 
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey 

745 



746 



Tsai 



requirements and challenges for immunoassay performance. Among the more promi- 
nent challenges for a DAT immunoassay is the ability to react with a desired panel of 
structurally related compounds with ideal levels of affinity while excluding the reac- 
tion with other similarly related structures. In certain cases, the desirable cross-reac- 
tivity characteristics may vary depending on the market segments, regulatory 
implications, and the goals of the DAT programs. Additionally, each of the biological 
sample matrices has unique requirements and challenges for developing a suitable 
DAT immunoassay. Good knowledge of the chemistry, metabolism, and cross-reac- 
tivity of the relevant substances is important for the apposite interpretation of the drug 
screening assays. These issues are of particular interest when evaluating immunoas- 
says for detecting cannabis abuse due to the complexity of cannabinoid chemistry and 
metabolism. Moreover, the performance and improvement in the gold standard GC/ 
MS reference methodologies can influence the overall assessment of cannabinoids 
immunoassays. 

The main objective of this chapter is to provide an overview of the design strat- 
egy, development, and applications of commonly used DAT immunoassays for can- 
nabinoid analysis. The factors that impact the performance and result interpretations 
of these immunoassays in cannabinoid screening are discussed. Examples of com- 
parative evaluations of cannabinoid immunoassays will also be reviewed. It has long 
been recognized that Cannabis -derived substances are the most frequently abused drugs 
worldwide ( 1-3). Likewise, cannabinoids continue to be the most widely investigated 
and extensively published illicit drugs. 

2. Commonly Used Immunoassays for Drugs-of-Abuse Screening 

All currently used immunoassay techniques for DAT screening have been devel- 
oped and refined over the past few decades. The reaction principles of these immuno- 
assays have been described in a number of publications and commercial product 
information documents. Therefore, this section will provide only a brief overview of 
the commonly used drugs-of-abuse screening techniques. 

The majority of DAT immunoassays are based on the competition of drug mol- 
ecules in the specimen and drug derivatives in the assay reagent for binding to a 
prespecified antibody reagent. The discriminatory power of the antibody-binding site 
gives the assay specificity, even though the cross-reactivity profile can be influenced 
by factors beyond the binding interaction alone. 

The immunoassay indicator for monitoring the binding interactions can be labeled 
drug-derivative, antibody, or an independently labeled molecule that can specifically 
bind to the antigen or antibody. The labels convey a measurable property to meet the 
performance requirements of the specific immunoassay. 

In general, the heterogeneous type of immunoassay contains excess labeled-bind- 
ing reagent in the reaction mixture, and the reaction outcome is determined by the 
relative fractions or activities of the "bound" (e.g., solid phase bound) labels. Thus, 
heterogeneous competitive immunoassays involve sequential incubation and separa- 
tion or washing steps but can generally achieve lower detection limits and wider dy- 
namic ranges. 



Immunoassays to Detect Cannabis Abuse 



147 



In contrast, the antibody-antigen reactions in the homogeneous immunoassay 
systems can modulate the physical properties or activities of the labels in solution or 
in a homogeneous suspension of particles. Such features allow the direct detection of 
the reaction outcome in the original reaction mixture. Therefore, the homogeneous 
immunoassays can be more readily adapted to screening large amounts of samples 
using automatic analyzers. During the design, development, and validation of an 
immunoassay, the labeled reagent, the specific binding partner, and the reaction modu- 
lators are prepared in specified and stabilized reagent formulations. In an actual test- 
ing, sample and reagents are processed according to the parameters optimized for the 
application of the immunoassay on the specific analyzer system. 

2.1. Homogeneous Competitive Immunoassays 

In recent years, routine laboratory screening of drugs of abuse in urine has mainly 
been carried out by homogeneous competitive immunoassays. The most widely used 
homogeneous drug-testing immunoassay technologies include enzyme-multiplied 
immunoassay technique (EMIT), fluorescence polarization immunoassay (FPIA), kinetic 
interaction of microparticles in solution (KIMS), and cloned enzyme donor immunoassay 
(CEDIA). The major assay labels and the technologies are implied in the respective 
immunoassay nomenclature. 

The assay principle of EMIT is based on the modulation of enzyme activities by 
the binding of specific antibodies to the enzyme-labeled drug derivatives (4-6). Cur- 
rently, EMIT-based DAT immunoassays can be purchased from several companies, 
and a common enzyme of choice is the genetically modified glucose-6-phosphate 
dehydrogenase (rG6PDH). The oxidation of enzyme substrate G6P to form 
glucuronolactone-6-phosphate is coupled with the reduction of the cofactor nicotina- 
mide adenine dinucleotide (NAD) to NADH. In the absence of drugs in the sample, 
the antibodies bind to the enzyme-labeled drugs and inhibit the enzymatic activity. 
Free drugs in the specimen compete for antibody binding, so fewer antibodies are 
available for binding to the drug-enzyme conjugates and enzymatic activity is less 
inhibited. The rate of NADH production, as reflected by the change in absorbance at 
340 nm, is directly related to the G6PDH enzyme activity. Therefore, the change of 
absorbance can be plotted vs the corresponding calibrator concentration to construct a 
calibration curve for running a semi-quantitative assay. The assay can also be run 
qualitatively by comparing the sample rate to the calibrated cutoff rate. 

The measurement of FPIA relies on detecting the degree of polarization of the 
emitted fluorescent light when the fluorophore label is excited with plane-polarized 
light (7,8). FPIA requires a specific FP photometer (9,10). A polarization filter (rota- 
tional) and an emission filter (stationary) enables the photomultiplier tube to read 
emitted parallel and perpendicular polarized light. The degree of polarization is 
dependent on the rate of rotation of the drug-fluorophore conjugate (tracer) in solu- 
tion. Small molecules such as tracers can rotate rapidly before light emission occurs, 
resulting in depolarization of the emitted light. When bound to the antibody, the tracer 
rotates more slowly and the level of fluorescence polarization is higher. An optimized 
amount of the tracer competes with free drugs in the sample for binding to a limited 
amount of antibodies. Hence the drug concentration is inversely related to the degree 



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of polarization. Calibrators containing known amounts of drugs interact with the trac- 
ers and antibodies to produce a calibration curve relating drug concentrations to arbi- 
trary "milliPolarization" units (mP). The interactions of the drugs in the specimen, the 
tracers, and the antibodies under the same condition controlled by the analyzer yield 
mP units that can be correlated with the drug level in the specimen by making a com- 
parison with the calibration curve. 

The principle of microparticle agglutination-inhibition tests has been applied to 
various drug screening assay formats (11-15). One KIMS DAT format is based on the 
competition of microparticle-labeled drug derivatives and the free drugs in the speci- 
men for binding to a limited amount of free antibodies in solution (14,15). The drug 
conjugates are labeled with microparticles through covalent coupling. These drug con- 
jugates react with free antibodies and form particle aggregates that scatter transmitted 
light. The KIMS-II format contains soluble polymer drug derivative conjugates and 
microparticle-labeled antibodies ( 16). The binding of the conjugates to the antibodies 
promotes the aggregation and leads to subsequent particle lattice formation. In both 
cases, the aggregation reaction in solution results in a kinetic increase in absorbance 
values. Free drugs in the sample compete for antibody binding and inhibit the particle 
aggregation. The absorbance difference between a defined initial reading and final 
reading decreases with increasing drug concentration, and the signal generated can be 
monitored spectrophotometrically. The assay can be run qualitatively in comparison 
with the cutoff calibrator. The assay can also be run semi-quantitatively using four or 
five levels of calibrators to construct a calibration curve via a logit/log fitting func- 
tion. 

The measurement of CEDIA is based on the antibody modulation of the comple- 
mentation of two inactive polypeptide fragments to associate in solution to form an 
active enzyme. The fragments of the recombinant microbial (3-galactosidase are called 
the the enzyme donor (ED) and enzyme acceptor (EA). The binding of antibodies to 
the drug-ED conjugates can inhibit the spontaneous assembly of active enzymes 
(17,18). The CEDIA reagent composition includes the lyophilized EA and ED re- 
agents and their respective reconstitution buffer solutions. The antibody binding to 
drug-ED conjugates in the analyzer reaction cuvet prevents the formation of active 
enzymes in the cuvet. Conversely, free drugs in the specimen compete for antibody 
binding and allow the drug-ED conjugates to reassociate with the EA fragments. There- 
fore, the drug concentration is proportional to the amount of active enzyme formed. 
The enzyme catalyzes the hydrolysis of selected substrate such as chlorophenol red- 
(3-D-galactopyranoside, and the resulting absorbance rate change is measured as a 
function of time (mA/min). CEDIA assays can be run either qualitatively or semi- 
quantitatively based on an appropriate calibration curve. 

2.2. Heterogeneous Competitive Immunoassays 

A variety of heterogeneous immunoassay formats have been explored and devel- 
oped; among those broadly used for DAT are the radioimmunoassay (RIA) and the 
enzyme-linked immunosorbent assay (ELISA). Again, the assay labels and principles 
of these technologies are implied in their respective immunoassay nomenclature. 

Different formulations of RIA have been developed and evaluated for the detec- 
tion and quantification of abused drugs in a myriad of biological matrices, including 



Immunoassays to Detect Cannabis Abuse 



149 



urine, blood, serum, plasma, saliva/oral fluids, meconium, hair, and fingernails 
(6,14,15,18-23). The most commonly used radiolabel is 125 I. Several methods, such as 
the double-antibody approach and the coated-tube technique, were developed to 
facilitate the effective separation of free, radiolabeled drug derivatives from the bound 
complex. The double-antibody approach employs a second antibody to bind the pri- 
mary antibody and precipitate the complex formed by primary antibodies and 125 I-drug 
derivatives. The coat-a-count technique utilizes precoated primary antibodies in the 
reaction tube to allow the removal of the free radiolabeled drug derivatives in the 
supernatant. The radioactivity from the bound 125 I-labeled drugs in the precipitated 
complex, or the bound solid phase, is inversely proportional to the amount of drug in 
the sample. Thus, the drug concentration in the sample can be determined by math- 
ematically comparing average counts per minute (CPM) obtained from the sample 
with the CPM obtained from the positive reference standard. For quantification, a 
dose-response curve can be established by plotting standard concentrations against 
corresponding B/B (B = CPM obtained from the zero-dose control). Alternatively, a 
standard curve can be constructed by plotting logit of [B/B ] vs corresponding values 
of log e [drug concentration]. 

Various commercial or esoteric ELISA methodologies have been utilized for 
DAT in forensic, clinical, and toxicological laboratories. Currently, there are approxi- 
mately a dozen companies that offer an array of ELISA kits for an extended menu of 
drug analysis. Commercial ELISA kits can be applied to test forensic matrices such as 
urine, blood, serum, oral fluid, sweat, meconium, bile, vitreous humor, and tissue 
extracts (24-29). In recent years, the highest volume of laboratory-based oral fluid 
DAT has been performed with qualitative microplate enzyme immunoassays (27). 
Most of the ELISA kits use high-affinity capture antibody-coated microtiter plates (or 
12- x 8-well strips) and enzyme-labeled drug derivatives. One commonly used en- 
zyme is horseradish peroxidase, which catalyzes the reduction of peroxide and the 
oxidation of the substrate tetramethylbenzidine. The reaction is stopped by diluted 
acid, and the resulting color can be measured by absorbance at 450 nm. A few ELISA 
tests offer the option to qualitatively determine the absence or presence of drugs by 
visually comparing the sample well reaction color to that of the cutoff calibrator and 
appropriate negative and positive controls. The drug concentration is inversely pro- 
portional to the amount of signal produced. Various instrument platforms for ELISA 
are available with optional data management software. 

Immunoassays with chemiluminescence detection techniques have the advan- 
tages of lower detection limits, and the signals can be further amplified if coupled 
with an enzyme label (30). An example of commercial enzyme-enhanced chemilumi- 
nescence assay for DAT is the IMMULITE® cannabinoid assay. The chemilumines- 
cent substrate (1,2-dioxetane) is destabilized by the enzyme (alkaline phosphatase), 
and the unstable dioxetane intermediate will emit light upon decay back to the ground 
state. Although this is a heterogeneous immunoassay in principle, the analyzer for 
Immulite assay utilizes a test unit that contains polystyrene beads to capture antibody 
and hence separate the reaction components within the unit. The tube is the reaction 
vessel for incubations, washes, and signal development. The photon count is math- 
ematically converted to analyte concentration by the external computer. 



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2.3. Point-of-Collection Drug Immunoassays 

In the early phases of drug-testing program implementation, the majority of on- 
site, point-of-care, or point-of-collection (POC) DAT programs employed instrument- 
based immunoassays that were performed at "on-site, initial screening only testing 
facilities" (31-33). Pioneers of noninstrumented DAT on-site testing have been avail- 
able since the early 1980s, yet the markets for single-use DAT devices only became 
mature in the 1990s (12,13,34^5). In recent years, there has been an increase in the 
numbers, and especially in the distributors, of on-site drug testing products. The more 
extensive list of the commercial POC drug testing (POCT) products can be found in 
reports that include the initial evaluation or inventory of the contemporary on-site 
testing products in their study protocols (35-37). 

In general, there are three major categories of POCT products. One type consists 
of the microparticle agglutination-inhibition based assays with ready-to-dispense liq- 
uid reagents (13,37). Another category of POCT product contains both liquid reagent 
and membrane-immobilized reagent, such as membrane enzyme immunoassay or the 
ASCEND® multi-immunoassay (37,38). The most widely commercialized and com- 
monly employed immunoassay for on-site DAT is the membrane-based, dry chemis- 
try, one-step lateral-flow immunochromatography (37,39^5). The lateral flow test 
strip configurations include the colloidal gold-based test strip configuration (40,41,46) 
and latex-enhanced immunochromatography (39,47). A number of readers have also 
been marketed to assist in interpreting and/or recording the results of the POC test 
strips. In addition, a few nonconventional immunoassay technologies have been ex- 
plored to utilize small instruments with quantitative ability for on-site drug testing or 
monitoring (48-50). 

The advantages generally cited for using POCT products include the speed in 
obtaining a qualitative determination and the ease of use. Many of the POCT devices 
are self-contained, panel-testing devices that can be stored at room temperature. 
The ready-to-use devices depend on precalibration during manufacturing. Although 
the devices generally have less clear differentiation in near-cutoff result reading, these 
assays in routine use have been shown to provide comparable performance with con- 
ventional immunoassays in most drug-screening settings that demand a rapid turn- 
around time. 

3. Cannabinoid Immunoassays 

3.1. Cannabinoid Test System 

Cannabis is by far the most widely cultivated, trafficked, and abused illicit drug 
in the world (1-3). According to the recent Drug Abuse Warning Network update 
(51), the rate of drug abuse-related emergency department visits involving marijuana 
rose 139% nationally from 1995 to 2002. As reported in the Drug Testing Index series 
published by Quest Diagnostics (52), cannabinoid analysis has always had the highest 
"drug positivity rate by drug category" among all of the abused drugs tested in work- 
place drug-testing programs. Likewise, cannabinoid assays are among the most fre- 
quently performed tests in society drug testing, behavior toxicology, and criminal justice 
testing. 



Immunoassays to Detect Cannabis Abuse 



151 



Cannabinoid is a term originally used to denote the unique C 21 compounds found 
in the plant Cannabis sativa L. (53,54). Recent progress in cannabinoid research has 
been extended to various ligands of the cannabinoid receptors and related compounds, 
including the transformation products of cannabinoids, synthetic cannabinoid ana- 
logs, and the endocannabinoids, namely, the endogenous ligands of the cannabinoid 
receptors (55-58). As reflected by the profuse publications in cannabinoid chemistry, 
tremendous efforts have been invested in the isolation of the chemical constituents 
and the investigation of the structure-activity relationships of the cannabinoids. 

The Cannabis plant contains more than 400 chemical compounds belonging to 
18 different classes, including more than 60 phytocannabinoids that contain a typical 
C 21 structure with pyran and phenolic rings (53-60). Most of the phytocannabinoids 
belong to several subclass types, including the tetrahydrocannabinol (A 9 -THC and A 8 - 
THC), cannabinol (CBN), cannabidiol (CBD), cannabichromene (CBC), and 
cannabigerol types (Fig. 1). The main active constituent of cannabis, and the primary 
psychoactive cannabinoid is A 9 -THC (55-59). The nomenclature A'-THC is based on 
the dibenzopyran numbering system; the same compound can also be called A'-THC 
according to the monoterpene numbering system (54). Immunoassays for detecting 
cannabis abuse in urine have been designed to detect THC metabolites and are gener- 
ally referred to as the cannabinoid assay or THC assay. 

In The Federal Register (21 CFR 862.3870), the cannabinoid test system is iden- 
tified as "a device intended to measure any of the cannabinoids, hallucinogenic com- 
pounds endogenous to marihuana, in serum, plasma, saliva, and urine. Cannabinoid 
compounds include A 9 -THC, CBD, CBN, and CBC. Measurements obtained by this 
device are used in the diagnosis and treatment of cannabinoid use or abuse and in 
monitoring levels of cannabinoids during clinical investigational use." Quantitatively, 
the most important cannabinoids present in the cannabis plant are THC and the much 
less prominent constituents CBD, CBN, and CBC (58-60). Immunoassays developed 
to detect THC metabolites usually have certain degrees of cross-reactivity with CBN 
but have minimal or no detectable level of cross-reactivity with the ring-opened com- 
pounds such as CBD, CBC, and cannabigerol. 

In analyzing 35,312 cannabis preparations confiscated in the United States 
between 1980 and 1997 (59), ElSohly et al. reported that the average concentrations 
for THC were 3.1% in marijuana (herbal cannabis), 5.2% in hashish (cannabis resin), 
15.0% in hash oil (liquid cannabis), and 8.0% in sinsemilla (unfertilized flowering 
tops from the female Cannabis plant). The average THC content of these cannabis 
preparations all showed significant increase over the years. The outcome of a cannab- 
inoid test can be affected not only by the analytical performance but also by drug- 
administration factors such as the potency (%THC) of the drug consumed, the route of 
administration, the methods, vehicles, and frequency of drug intake, the timing of 
drug use and sample collection, the type of samples tested, and the pharmacokinetics 
and pharmacodynamics of cannabinoids (23,61-73). 

3.2. Cannabinoids: Pharmacokinetics and Drug Analysis 

Cannabinoids immunoassays for each type of biological matrix have to be 
designed and interpreted in the context of A 9 -THC absorption and metabolism. The 



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S' j* 



(Dibenzopyran numbering) A*-THC = A'-THC (Monoterpene numbering) 
(Positional Isomer A 8 -THC = A*-THC) 

A 9 -THC (R, = H,R 3 = H) 

A 9 -THC acid A (R, = COOH, R 3 = H) 

A^-THC acid B (R, = H, R 3 = COOH) 




K, =H or COOH 

R 2 = mostly C 3 or C 5 side chain 

R 3 = H or CH 3 



Fig. 1. Chemical structure of naturally occurring cannabinoids. 21 CFR 862.3870 
defines a "cannabinoid test system" as "a device intended to measure any of the 
cannabinoids, hallucinogenic compounds endogenous to marihuana, in serum, 
plasma, saliva, and urine. Cannabinoid compounds include A 9 -tetrahydrocannabinol, 
cannabidiol, cannabinol, and cannabichromene. Measurements obtained by this 
device are used in the diagnosis and treatment of cannabinoid use or abuse and in 
monitoring levels of cannabinoids during clinical investigational use." 

pharmacokinetics, metabolism, and excretion profiles of cannabinoids have been com- 
prehensively studied and reported (20,21,23,54-58,61-76). THC is known to be 
extensively metabolized to a large number of compounds, even though most of the 
compounds are inactive (73-77). As shown in Fig. 2, A 9 -THC is mainly hydroxylated 



Immunoassays to Detect Cannabis Abuse 
Glucuronide Conjugates^ 



153 



1 1-nor-A -THC- 
carboxylic acid 



8p,ll-dihydroxy-A -THC 



COOH 

t 

ll-hydroxy-A 9 -THC 

CH2OH Fatty acid conjugates 

I 

Glucuronide Conjugates 



hydroxy lati on 
& oxidation 




8-a-hydroxy-A -THC 



A -THC (A -Tetrahydrocannabinol) 



Fig. 2. Metabolic transformation of AMetrahydrocannabinol (THC). (Note: Analogous 
pathways exist for A 8 -THC and cannabichromanon.) 



at the allylic positions (C-ll and C-8) and further oxidized. Oxidation also occurs at 
the pentyl side chains. Similar biotransformation pathways exist for A 8 -THC (C-7 and 
C-ll) and other cannabinoids. Smaller quantities of other metabolites are produced by 
minor metabolic pathways. 

It has been well established that the oxidative metabolism of aliphatic, benzyl, 
phenylethyl, and allylic alcohols to the corresponding carbonyl compounds is cata- 
lyzed by numerous cytochrome P450 (CYP) enzymes with overlapping substrate speci- 
ficity (74-77). In human liver microsomes, the C-ll position of THC is metabolized 
by CYP2C subfamilies, and the C-7 and C-8 positions are metabolized by the CYP3A 
isoforms. Pharmacogenetic studies have demonstrated the significant interindividual 
variations in CYP-catalyzed metabolism. Metabolite composition varies with speci- 
men source and experimental conditions. The presence of various amounts of metabo- 
lites in a given biological matrix and their relative binding affinity to the given 
antibodies may both contribute to different degrees of cumulative total binding activi- 
ties for different immunoassays. 

Initial metabolism following inhalation takes place in the lungs and liver to 11- 
hydroxy-A 9 -THC (1 1-OH-THC), which is subsequently oxidized in the liver through 
11-oxo-THC as an intermediate to ll-nor-A 9 -tetrahydrocannabinol-9-carboxylic acid 
(THC-COOH) and other inactive metabolites. The major THC metabolite in plasma 
and urine following smoking is THC-COOH, whereas a higher level of 1 1-OH-THC 
is present in blood after oral ingestion (61-70). In frequent smokers, residual levels of 
THC and THC-COOH have been detected for an extended period of time after cessa- 



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tion of drug use. Most commercial cannabinoid immunoassays are calibrated with the 
major metabolite, THC-COOH, but also have to meet the product design specifica- 
tions for the antibody cross-reactivities with THC drug and other THC metabolites 
(e.g., 8-0C-hydroxy-A 9 -THC, 8-(3-hydroxy-A 9 -THC, 8-0,1 l-di-hydroxy-A 9 -THC, and 11- 
OH-THC). Although immunoassays developed for urinalysis can be adapted for alter- 
native specimen testing, the cross-reactivity characteristics selected for urine drug 
screening may not be optimal for other biological matrices. The antibody reactivity 
with the parent A 9 -THC is especially important for oral fluid testing. 

Glucuronic acid conjugation with A 9 -THC and its hydroxylated and carboxy- 
lated metabolites generates water-soluble compounds; thus THC-COOH and other 
metabolites are mainly excreted as their glucuronide conjugates in urine and meco- 
nium (78-86). In routine cannabinoid urinalysis, presumptive positive samples are 
confirmed by GC/MS detection of free THC-COOH, which was liberated from its 
glucuronide by chemical or enzymatic hydrolysis prior to sample extraction. Kemp et 
al. (83) evaluated different hydrolysis methods in the quantification of A'-THC and its 
major metabolites in urine and demonstrated the inefficiencies of base hydrolysis on 
the hydroxylated compounds. There is a species-dependent glucuronidase activity; 
hydrolysis with Escherichia coli glucuronidase greatly increased the concentration of 
free A 9 -THC and free 11-OH-THC in urine collected following marijuana smoking. 
The concentration of free THC-COOH was not significantly affected by hydrolysis 
method. 

Gustafson et al. (81) analyzed plasma samples collected in a controlled oral A 9 - 
THC administration study and found increases of 40% for 11-OH-THC and 42% for 
THC-COOH concentration between hydrolyzed and nonhydrolyzed results. ElSohly 
and Feng (79) compared the effect of hydrolysis on the detection of A 9 -THC metabo- 
lites in meconium and demonstrated significant levels of 11-OH-THC and 8-(3,ll- 
diOH-A 9 -THC after hydrolysis but none without hydrolysis. Among the samples 
examined, one showed an almost 50% increase in THC-COOH concentration as a 
result of enzymatic hydrolysis. Analysis of several meconium specimens that "screened 
positive for cannabinoids but failed to confirm for THC-COOH" showed significant 
amounts of 1 1-OH-THC and 8-(3,l l-diOH-A 9 -THC. Hence, the authors suggested that 
GC/MS confirmation of cannabinoids in meconium should include analysis for these 
metabolites in addition to THC-COOH. 

The ratio of glucuronidated vs free THC-COOH in the sample at the time of 
immunoassay analysis may influence the comparative immunoassay evaluation. 
Employing LC/MS/MS with and without enzyme hydrolysis, Weinmann et al. (86) 
determined that the molar concentration ratio of glucuronidated vs free THC-COOH 
in urine samples of cannabis users was between 1.3 and 4.5. In studying the profiles of 
THC metabolites in urine, Alburges et al. (78) observed that all of the THC-COOH 
excreted in the first 8 hours from an infrequent user was in conjugated form, whereas 
free THC-COOH could be detected in urine from a frequent user for at least 24 hours. 
Skopp et al. (84,85) investigated the dynamic changes of free vs conjugated THC- 
COOH in urine and found that free THC-COOH was not detected in 20 out of 38 
fresh, authentic samples. At the end of the observation period, 5-81 ng/mL of THC- 
COOH was detectable in 1 1 samples that initially tested negative. The results showed 



Immunoassays to Detect Cannabis Abuse 



155 



that THC-COOH and THC-COOglu, as well as total THC-COOH concentrations, might 
undergo dynamic changes in urine samples depending on pH and storage conditions 
(85). THC-COOH is the primary urinary cannabinoid analyte quantified by GC/MS 
after hydrolysis and extraction. In contrast, immunoassays are calibrated for THC- 
COOH detection, and the antibodies generally have variable degrees of cross-reactiv- 
ity towards the glucuronidated metabolites. 

By and large, the immunoassay result is based on the sum of various levels of 
antibody immunoreactivities in the sample matrix tested. The overall reactivity (as 
expressed in apparent THC-COOH concentration or calibrator-equivalent unit) can be 
affected by various factors. Among the pivotal factors is the design of the chemical 
structures for both the drug derivatives for reagent conjugation and the immunogens 
used for antibody generation. 

3.3. Immunogen Strategies for Antibody Generation 

The overall analytical sensitivity and specificity of an immunoassay is, to a sig- 
nificant extent, related to the characteristics of the antibody used in the assay. Because 
drugs such as cannabinoids are small molecular weight haptens, a carrier protein is 
needed to produce an effective Immunogen. The site of linkage on the drug molecule 
to the protein carrier can determine the reactivity of the resulting antibodies. The speci- 
ficity of an antibody is usually directed toward those structures on the hapten that are 
distal to the linkage group. Thus, the linkage site allows haptens to be coupled to the 
carrier in such a way that characteristic functional groups are exposed for antibody 
generation (20,21,87-89). 

Figure 3 shows the published linkage sites for coupling cannabinoid haptens to a 
carrier protein. These linker groups include those out of the CI -position, the C2-posi- 
tion, the C9-position, and the C5' -position of the THC-COOH compound or a very 
closely related compound. Various immunogen design structures were described in 
the National Institute on Drug Abuse Research Monographs 7 and 42 (20,21 ). Most of 
these antibodies were used for the development of RIAs with the exceptions of immu- 
nogen structures depicted for developing EMIT assay with the enzyme "pig heart malate 
dehydrogenase." There are a few major families of US/European/World patents for 
cannabinoid immunoassays along with claims for the structures of drug derivatives 
and/or immunogens. The patent families include those for Abbott's FPIA and those 
for Roche's RIA, enzyme immunoassay, FPIA, and KIMS cannabinoid assays (88,89). 

Salamone et al. (87) comprehensively reviewed the selectivity of different im- 
munogen structures and also described an approach to generate antibodies with a broader 
spectrum of cross-reactivities towards THC metabolites by "sequential immunization" 
and by designing a noncannabinoid, benzpyran core, immunogen. Taken together, the 
antibody generation approaches can be summarized as follows: 

1. In general, antibodies generated from immunogens with the linkage position out of 
the C1-, C2-, or C5'-positions are more selective for the cyclohexyl ring, hence they 
usually display high selectivity for the unconjugated form of THC-COOH. The cross- 
reactivities for the 8-, 9-, and 11 -substituted metabolites is lower because of the high 
recognition of the antibodies for this part of the molecule. Likewise, the cross-reactivi- 
ties with the glucuronidated compounds are lower because the ether bond forms between 



756 



Tsai 



US 5144030, 1992, US 5264373, 1993, (Abbott) FPIA tracer 

... US 53 1 50 1 5, 1 994, (Roche) FPIA tracer and irnmunogen; 
US 5463027, 1 995, (Abbott) FPIA immunogen 
Rowley, 1976 (Syva) EMIT immunogen 

h* Tsui ' ,974 > Rowley, 1976, Roger, 1978, DeLaurentis (Syva), 1982, 

^"OO no 



U'll 




US 4438207, 1984, (Roche) RIA immunogen 
US 4833073, 1989 & US 521 9747. 1993, 
(Roche) EIA derivative 
Teal, 1974, 1975, Tsui, 1974, Chase 1976 



Tsui, 1974, Gross, 1974, Soars, 1976 



(Cook, 1974) 




The Benzpyran core 

US 5817766, 1998, (Roche) I A immunogen 

Fig. 3. Immunogen strategies for the generation of anticannabinoid antibodies: 
common sites of linkage of cannabinoid haptens to a carrier protein. (From refs. 
4,19,20,83-85.) 



glucuronic acid and the hydroxyl moiety at C-l 1 for 1 1-OH-THC, and the ester bond 
forms between the glucuronide and the carboxyl moiety at C-l 1 for THC-COOH. 

2. On the other hand, antibodies generated by immunogens with the C-9 position linkage 
are less selective for the cyclohexyl ring. Nevertheless, these antibodies typically show 
better binding to the 8-, 9-, and 1 1 -substituted metabolites, as well as improved bind- 
ing to their corresponding glucuronides. The antibodies also exhibit some selectivity 
for the cannabinoid nucleus in this region. These types of antibodies can be selected 
for high cross-reactivities for some, but not all, of the 8-, 9-, and 1 1-hydroxylated 
metabolites. 

3. To increase the spectrum and degree of cross-reactivities for THC metabolites, a 
noncannabinoid immunogen was designed not to hold the antigenic determinants of 
the cyclohexyl ring, and hence the resulting antibodies will be indifferent to the 
cyclohexyl portion of the cannabinoid nucleus. Such a bicyclic immunogen contained 
only the structure of the benzpyran core. By eliminating the portion of the molecule 
that undergoes extensive metabolism from the immunogen and by preserving the core 
structure, antibodies with higher cross-reactive values with positive clinical samples 
can be generated. The resulting antibodies from the benzpyran core immunogens all 
showed broader cross-reactivities towards the 8-, 9-, and 1 1-hydroxylated metabolites. 



Immunoassays to Detect Cannabis Abuse 



157 



The broad-spectrum antibodies can be utilized beyond the development of 
immunoassays. Feng et al. (80) immobilized THC antibody that was generated from 
the benzpyran core immunogen to prepare immunoaffinity chromatography for devel- 
oping a simpler extraction procedure for A 9 -THC and its metabolites from various 
biological specimens. Good recovery was achieved by simultaneous extraction of A 9 - 
THC and its major metabolites, including THC-COOH, 1 1-OH-THC, and 8-(3,l 1-diOH- 
A 9 -THC, from plasma or urine after enzyme hydrolysis. A similar approach was also 
used for meconium analysis and confirmed that 1 1-OH-THC (80) is indeed an impor- 
tant metabolite in meconium. 

The evolution of assay specificity can also be observed from the review of three 
decades of publications regarding cannabinoid immunoassays. In the earlier stages of 
drug immunoassay development, immunogens were used to produce polyclonal anti- 
bodies from selected animals. Naturally, polyclonal antibodies have broader cross- 
reactivities that are collectively contributed by a range of antibody affinity, avidity, 
and binding characteristics. The overall cross-reactivity manifestation can vary a bit 
from animal to animal and may change slightly over different time periods. Thus, it is 
not unusual for large pools of polyclonal antibodies to be validated and sequestered. 
Most current DAT immunoassays use monoclonal antibodies that are much more 
selective and specific and possess consistent quality. High specificity toward the tar- 
get THC-COOH may increase overall immunoassay specificity at the expense of sen- 
sitivity. Thus, high antibody specificity may have the disadvantage of lower detection 
rate for clinical samples that contain THC-COOH near the screen cutoff concentra- 
tion. Broad-spectrum monoclonal antibodies can possess the advantages of both mono- 
clonal antibody consistency and the broader cross-reactivity profile. Nevertheless, the 
increased immunoassay sensitivity resulting from the higher values of THC-COOH 
equivalents might have the disadvantage of producing unconfirmed positives and might 
need a lower GC/MS cutoff (87). 

Bearing in mind the variations in the relative percentages and forms of A 9 -THC 
metabolites present in the testing samples, both the detection and confirmation rates 
can have trade-offs, especially for near-cutoff samples. The ultimate goal for a can- 
nabinoid immunoassay design is to balance the assay sensitivity and specificity for its 
comparative performance to the GC/MS analysis according to their respective cutoff 
guidelines and regulations. 

3.4. Regulations and Guidelines 

Globally, various guidelines for substance abuse management have been devel- 
oped by government agencies, forensic societies, and clinical organizations. Some of 
the guidelines include more detailed technical and procedural recommendations for 
specimen collection and processing, initial drug screening, confirmation analysis, qual- 
ity control and assurance, and documentation and result-reporting requirements. 

In the United States, the federally regulated drug-testing programs are imple- 
mented and administered by the Substance Abuse and Mental Health Services Admin- 
istration (SAMHSA, formerly National Institute of Drug Abuse) and Department of 
Health and Human Services. The 1994 SAMHSA Mandatory Guidelines for Federal 
Workplace Drug Testing Programs (90) define initial test or screening test as "an 



158 



Tsai 



immunoassay test to eliminate negative urine specimens from further consideration 
and to identify the presumptively positive specimens that require confirmation or fur- 
ther testing." The guidelines mandate that the initial test "shall use an immunoassay 
which meets the requirements of the Food and Drug Administration (FDA) for com- 
mercial distribution." The guidelines also permit multiple initial tests (or rescreening) 
to be performed utilizing different immunoassays for the same drug or drug class 
under the stipulation that "all tests meet all Guideline cutoffs and quality control 
requirements." 

The regulated approach to initial screening "permits rapid identification of pre- 
sumptive positives within a framework of extensive quality control and offers a defined 
reference if the next step confirmation is required." This allows a process with a set 
"administrative cutoff for uniform comparison across different assay principles and 
various volumes of screening. The specified cutoff levels for cannabinoids testing were 
set at 100 ng/mL for immunoassays and 15 ng/mL for GC/MS in the first Mandatory 
Guidelines (53 FR 1 1970, 1988). The cutoff for immunoassay was lowered to 50 ng/mL 
in the subsequent version of the federal guidelines (91). In case a retest is required for 
a specimen or for the testing of Bottle B of a split specimen, the federal guidelines state 
that the retest quantification is not subject to a cutoff requirement. However, the retest 
"must provide data sufficient to confirm the presence of the drug or metabolite" (90). 

The proposed revisions for the next version of the Mandatory Guidelines ( 91, 92 ) 
will include regulations on specimen validity testing, POCT, and alternative specimen 
testing. Additionally, the new guidelines will expand the authorized confirmation 
method from only GC/MS to allow the use of additional confirmation technologies 
such as LC/MS. However, the new guidelines draft does not change the cutoff require- 
ments for cannabinoid testing. Other civilian drug-testing programs, such as the Col- 
lege of American Pathologists Forensic Urine Drug Testing laboratory accreditation 
program, allow the cutoff determinations be made according to the need of the labora- 
tory or to the intent of its clients' drug-testing programs. Generally speaking, even in 
nonregulated sectors, many drug-testing programs follow the cutoff defined by the fed- 
eral guidelines and require reporting positive results if both the initial immunoassay 
results and the GC/MS analysis are at or above their respective cutoff concentration. 

The provisions of the rules that affect US corporations may be imposed on their 
global employees. In contrast, countries in the European Union, Asia, and Australia 
differ in their concerns and strategies in relation to substance abuse problems. Surveys 
of DAT in European Union laboratories in the late 1990s indicated that a high percent- 
age of laboratories did not use or report cutoff (93-95). A few work groups in Europe 
have proposed consensus or country-specific guidelines and cutoffs, including drug- 
testing application-specific cutoffs, for DAT (see, e.g., refs. 96-98). The European 
Laboratory Guidelines for Legally Defensible Workplace Drug Testing were devel- 
oped by the European Workplace Drug Testing Society with an aim to "establish best 
practice" for laboratories within Europe "whilst allowing individual countries to oper- 
ate within the requirements of national customs and legislation" (98). For urine drug 
testing, the maximum cutoff for screening test and the confirmation cutoff recom- 
mended by the European Workplace Drug Testing Society for cannabis metabolites 
are the same as those mandated by the current SAMHSA guidelines. 



Immunoassays to Detect Cannabis Abuse 



159 



3.5. Comparative Evaluation of Cannabinoid Immunoassays 

3.5.1. General Evaluations 

Immunoassays for commercial applications have to be developed and manufac- 
tured in compliance with a number of regulations and quality-management require- 
ments. Currently, all projects for immunoassay research, development, and 
commercialization are required to follow the FDA Design Controls and Quality Sys- 
tem Regulations. The overall assay performance characteristics have to meet an array 
of predefined specifications with robust assurances at each of the design control mile- 
stone reviews in order to receive approval for proceeding to the next milestone. The 
manufacturers then submit data and statistical analyses in support of claimed perfor- 
mance parameters for the assay /device/instrument application to FDA for 5 10K review 
and approval for premarket clearance. Likewise, the manufacturers have to declare 
conformity and submit required data and documentations to the European In Vitro 
Diagnostic Directive for the immunoassays to be registered for the "CE mark." There 
are also country-specific processes for registration and approval for commercializa- 
tion in countries such as Japan and Canada. Additionally, many companies require 
external clinical trials during product development to simulate the performance in the 
field as well as to anticipate any potential findings or cross-reactivity issues not ob- 
served during the in-house development. To date, the majority of published evalua- 
tions of different immunoassay products have involved authentic clinical samples from 
either controlled drug-administration study or specimens collected for routine labora- 
tory drug testing (see, e.g., refs. 14, 15, 18, 35, 36, and 99-105). 

3.5.2. Cutoff Concentrations and Immunoassay Evaluations 

Because a cutoff is the concentration of drug below which all specimens are 
considered to be negative, the cutoff decision has a direct impact on the detection time 
window and the positive rate. The most commonly used method for immunoassay 
performance comparisons is to evaluate the so-called true-positive (TP), true-negative 
(TN), false-positive (FP), and false-negative (FN) of the assay. These results can then 
be used to calculate the specificity [TN / (TN + FP)] x 100%, sensitivity [TP / (TP + 
FN)] x 100%, efficiency [(TP + TN) / (TN + FP + TP + FN)] x 100%, or positive or 
negative predictive values of the assay. Because the criteria for either true or false are 
based on the comparison of immunoassay and GC/MS interpretation at their respec- 
tive screening and confirmation cutoff levels, the goals and strategies for balancing 
the relative performance around the selected cutoff concentrations are among the im- 
portant considerations for designing an immunoassay for cannabinoid testing. 

Traditionally, the cutoff decision can be made by considering the assay limit of 
detection or a predefined, higher concentration. Although not generally inferred in the 
context of drug testing, cutoff sometimes is used to refer to the analyte concentration 
at which repeated tests on the same sample yield positive results 50% of the time and 
negative results for the other 50%. In a near-cutoff zone as concentrations close to the 
cutoff value, some results may be positive or negative for different analytical method- 
ologies or for repeated testings using the same method. For most drug-testing pro- 
grams, the "administrative cutoffs" were chosen with the consideration that the cutoff 



760 



Tsai 



is sufficiently above the assay limit of detection, yet low enough to allow the detection 
of drug use within a reasonable time frame (90,91). One of the earlier concerns in 
setting the immunoassay cutoff for cannabinoids was the risk of falsely identifying 
urine samples as positive for individuals exposed to passive marijuana smoke. None- 
theless, further studies on passive inhalation have led to the conclusion that the levels 
of cannabinoids in the body from passive inhalation would not be enough to cause 
urine specimens from a non-marijuana user to test positive using a screen cutoff con- 
centration of 50 ng/mL (72,106,107). 

Several studies have since demonstrated that higher positive rates for marijuana 
detection were achieved by lowering the initial testing cutoff in urine ( 100-105). The 
sensitivity vs specificity tradeoff also reflects the fact that the target analyte specific- 
ity is related to the detection rate of cannabinoid immunoassays, especially for samples 
that contain THC-COOH concentrations between the mandated GC/MS cutoff and the 
mandated (or chosen) immunoassay cutoff levels ( 100-105,108-1 10). 

Luzzi et al. (Ill) investigated analytical performance of drug detection below 
the SAMHSA cutoffs and showed that the accuracy of urine drug-screening results 
between the SAMHSA-specified cutoffs and the precision-based cutoffs was less than 
the accuracy for specimens above the SAMHSA cutoffs. The use of the precision- 
based cutoff for clinical drug testing increased both the number of screen-positive 
specimens and the detection of specimens that yielded positive results on confirma- 
tory testing. However, the confirmatory rates for subcutoff-positive specimens were 
lower than for specimens screened positive at cutoff. When choosing 35 ng/mL as the 
subcutoff for EMIT screening, 90% of the subcutoff-positive THC specimens con- 
tained THC-COOH by GC/MS analysis. Similarly, Hattab et al. (112) stated that the 
immunoassay cutoff could be further lowered for detecting maternal and neonatal drug 
exposure. Using the lower thresholds, drugs were detected in 4-5% of the subjects 
that had screened negative at the conventional threshold concentrations. GC/MS analy- 
sis confirmed the presence of cannabinoids in 74% of urine specimens that rescreened 
positive at a lower cutoff. 

The target ranges of cutoff concentrations for alternative specimen testing are 
significantly lower than those for urine drug testing. The application of alternative 
specimens for drug testing is still an evolving field, and there have been ongoing dis- 
cussions and studies over recent years (23,27-29,42,45,113-122). In a prevalence study 
that compared positivity rates of oral fluid test results with urine test results for differ- 
ent drugs, the screening and confirmation cutoff concentrations selected for oral fluid 
cannabinoids testing were 3 and 1.5 ng/mL, respectively (27). The overall confirmed- 
positive prevalence rate for oral fluid testing at these cutoff concentrations was 3.2%. 
In comparison, the confirmed-positive prevalence rates for urine testing using 50 and 
15 ng/mL as the respective screening and confirmation cutoffs were 1.7% for feder- 
ally mandated urine testing and 3.2% for private sector workplace testing. 

With the low cutoff concentrations for oral fluid cannabinoid screening and con- 
firmation, oral fluid testing also has the potential to produce positive results from 
passive cannabis smoke exposure. In a controlled dosing study, Niedbala et al. reported 
that two individuals who were passively exposed to the smoke from 10 cannabis ciga- 
rettes produced positive screening results, which failed to test positive by GC/MS/MS 



Immunoassays to Detect Cannabis Abuse 



161 



(27). In a subsequent study with five cannabis smokers and four passive subjects, the 
authors observed a biphasic pattern of decline for THC in oral fluid specimens col- 
lected from active smokers, whereas the pattern of THC decline was linear in speci- 
mens collected from passive subjects (28). The authors concluded that the risk of 
positive oral fluid tests from passive inhalation is limited to a period of approx 30 
minutes following smoke exposure. 

In the latest version of the Proposed SAMHSA Guidelines (91), the following 
cutoff concentrations are recommended for detecting cannabis abuse: 

1. Initial tests: 

a. 1 pg marijuana metabolite/mg hair sample. 

b. 4 ng marijuana metabolite/sweat patch. 

c. 4 ng "THC parent drug and metabolites'VmL oral fluid specimen. 

d. 50 ng "THC metabolites'VmL urine specimen. 

2. Confirmation: 

a. 0.05 pg THC-COOH/mg hair sample. 

b. 1 ng THC parent drug/sweat patch. 

c. 2 ng THC parent drug/mL oral fluid specimen. 

d. 15 ng THC-COOH/ mL urine specimen. 

3.5.3. Correlation of Results From Cannabinoid Immunoassay 
and GC/MS Analysis 

A number of studies have been conducted to investigate how well results from 
cannabinoid immunoassays can correlate to GC/MS analysis and/or to select an 
appropriate cutoff value for each of the initial test methods (99-105). In all cases the 
general correlations exist, yet the data points could be rather scattered. Generally speak- 
ing, the correlation coefficients are more sensitive to the change of sample groups, in 
which the distributions in the relative concentrations of THC-COOH and other cross- 
reacting compounds varies. 

The relative concentrations of THC metabolites in plasma and urine have been 
studied to determine if a temporal relationship could be estimated between marijuana 
use and metabolite excretion (65,69). With the addition of the (3-glucuronidase 
hydrolysis step in the extraction protocol, the presence of significant quantities of 
THC and 11-OH-THC in urine could be demonstrated (69). The relative concentra- 
tions of THC-COOH and 1 1-OH-THC can be shown in a scatter plot when all data for 
urinary THC-COOH and 1 1 -OH-THC concentrations published in the article by Manno 
et al. (69) were used to create the plot shown in Fig. 4. For samples with THC-COOH 
levels closely surrounding the 15 ng/mL cutoff, the relative cross-reactivities of an 
immunoassay with 11-OH-THC, THC-COOH, and their relative abundance may con- 
tribute to the immunoassay outcome by rendering the results false positive or false 
negative when compared to a fixed GC/MS value of THC-COOH. 

In addition to the interindividual metabolism and metabolite variability, the cor- 
relation of immunoassay and GC/MS results can also be influenced by the total per- 
formance characteristics of not only the screening but also confirming techniques used 
(123-127). Because all analytical techniques have an acceptable range of imprecision, 
it is essential to note that a value generated from immunoassay or GC/MS analysis is 

















• 










































♦ 




























+ 

♦ 

* 

* 

* 

*> 




























- 

• 
♦ 


























« 








♦ 


♦ 












+ 


* 


* 






* 


♦ 


























♦ 












*» * _ _ 
















i 1 


i 



50 100 150 200 250 300 350 400 450 500 550 600 650' 700 

THC-COOH (ng(mL) 



Fig. 4. Relative concentrations of THC-CODH and 1 1-OH-TCH in cannabinoids containing urine samples. 
(Adapted from data from ref. 65.) 



Immunoassays to Detect Cannabis Abuse 



163 



Table 1 

Examples of the AACC/CAP Forensic Urine Drug Testing (Confirmatory) 



Survey Results 






(Vltcll 1 


C c\c±\t i c if^nt c\\ 
cue 1 1 1 L id 1 1 Ul 


1 C\\KI \I7K 1 IP* 
LUVV V cl 1 UC 


1 — 1 1 oh \/a i ic* 


Survey 


No l^hw 


( na/in 1 ) 


v^ri^Hon (°/rt) 

V Cl 1 1 Cl L 1 V J \ \ \ l\i f 


fnp/m 1 ) 

\ '(y ' ' ' *~l 


fnp/m 1 ) 


UDC-l, 2003 


128 


514.61 


16.9 


247.3 


718.8 




112 


77.18 


10.9 


53.9 


101.0 




111 


10.6 


12.1 


7.4 


14.3 


UDC, 2002 


113 


91 


13.7 






(year-end 


127 


591 


15.0 






critique) 


118 


97 


12.4 








122 


95 


11.2 








109 


36 


12.7 








126 


14 


12.7 








145 


13 


13.8 







Data were obtained with permission from American Association for Clinical Chem- 
istry/College of American Pathologists (AACC/CAP) forensic urine drug testing (confir- 
matory) Survey UDC-A of 2003 and Survey 2002 year-end critique for A' J -THC-COOH. 



not an absolutely fixed number. These analytical techniques all have to be validated 
and meet a host of quality-control and quality-assurance requirements. Similar to the 
requirements for proper utilization of immunoassays, knowledge of the advantages 
and potential pitfalls of different GC/MS systems as well as ionization and detection 
modes would facilitate proper optimization for the accuracy of compound quantifica- 
tion and identification (124). 

Because GC/MS involves multiple steps of extraction, derivatization, and quan- 
titative analysis, the laboratory has to determine the acceptable criteria for replicate 
analysis. Generally, the repeatability and reproducibility of GC/MS in a certified labo- 
ratory are excellent, even though there are interlaboratory variabilities among the cer- 
tified laboratories. For years, the College of American Pathologists and American 
Association for Clinical Chemistry have been conducting quarterly surveys and year- 
end critiques for all certified laboratories. The survey results of THC-COOH analysis 
for year-end 2002 and the first quarter of 2003 are listed in Table 1. The results are 
fairly consistent over the years, and the interlaboratory coefficient of variation has 
been approx 10-15%. Statistically, the variations may not significantly affect the con- 
firmation of presumptive positives, even though the confirmation rate for near-cutoff 
samples can be more readily affected. 

A semi-quantitative immunoassay produces a numerical concentration that 
approximates the total amount of THC-COOH along with associated metabolites in 
the specimen, namely, a value for apparent THC-COOH equivalent. The results of 
unknown clinical samples are calculated by the automatic analyzers based on a cali- 
bration curve. The calibration curve is calculated from prevalidated equations for the 
best-fit curve. The claimed concentrations of calibrators must be established by repeated 



764 



Tsai 



GC/MS analysis to ensure that the THC-COOH concentration in the calibrators stays 
within the acceptable range of GC/MS values for the entire duration of its shelf life. 

Table 2 shows a collection of analytical recovery data or imprecision data from 
various package inserts of commercial immunoassays. The nominal THC-COOH con- 
centration is the amount of THC-COOH compound spiked into urine for running the 
immunoassays, and the numerical value of apparent THC-COOH concentration is the 
average of replicate results obtained from the immunoassays. 

In general, the results of semi-quantitative immunoassays provide an indication 
of the levels of THC metabolites to assist in making dilutions for GC/MS analysis. 
How closely a semi-quantitative immunoassay result can match the nominal value is 
affected by a number of factors, including the quantitative accuracy of calibrators, the 
quantitative accuracy of the spiked samples for evaluation, the constituents of the 
specimens, the assay precision for the lot of reagents used, and the assay dynamic 
range. The results may no longer be semi-quantitative in that the absorbance changes 
of the immunoassay flatten out or reach the plateau (128). Commonly used commer- 
cial immunoassays offer applications for multiple cutoff choices to meet the require- 
ment of different drug-testing programs. Depending on the drug-testing program goals 
and preferences, the more frequently used cutoff concentrations for urinary cannab- 
inoid immunoassays are 20, 25, 50, and 100 ng/mL. 

In a study designed to understand the relationship of THC concentrations in oral 
fluid and plasma after controlled administration of smoked cannabis, Heustis and Cone 
observed that results from an RIA selective for THC were higher than those obtained 
from GC/MS . The mean ± standard deviation ratio of RIA to GC/MS concentration 
was 3.35 ± 2.16, with a range of 1.1-8.8 (23). The higher estimated THC concentra- 
tions in oral fluid by the RIA screen method were attributed to cross-reactivities of the 
THC RIA antibody to other cannabis constituents. In this study, THC RIA concentra- 
tions at 0.2 hour were generally 20-fold or more than those measured at 0.27 hour. 
With a 1.0 ng/mL screening cutoff concentration, the mean detection times by RIA for 
the 1.75% and 3.55% doses were 5.7+ 0.8 and 8.8 ± 8.3 hours, respectively. The au- 
thors also compared the excretion rates in three biological specimens from the same 
subject by GC/MS analysis of THC (for oral fluid and plasma) and THC-COOH (for 
urine) and reported half-life estimates of 0.8 hour for oral fluid, 0.9 hour for plasma, 
and 16.9 hours for urinary specimens. 

3.5.4. Stability of Cannabinoids in Biological Matrices 

Different stability studies have been conducted to investigate the stability of THC- 
COOH in urine or the stability of THC and THC-COOH in blood (84,85,129-134). 
The hydrophobic nature of cannabinoid molecules may lead to the loss of drugs in the 
specimen caused by surface adsorption to the specimen-handling and storage devices 
and containers. The loss of analyte from calibrator solutions can lead to inaccuracy of 
the analytical system (129). The stability of cannabinoids in immunoassay calibrator 
solutions and in urine samples has been extensively evaluated in various container 
materials at different temperatures (129-134). In addition to potential analyte loss to 
surface adsorption, the temperature and storage conditions can affect the stability of 
cannabinoids in specimens. Drug partition into strata when frozen in urine was observed 
and postulated to be due to the thermodynamics of the freezing process ( 131 ). 



Table 2 

Analytical Recovery of Semi-quantitative Cannbinoid Immunoassays at Different Cutoff Concentrations 2 



Nominal THC-COOH (ng/mL) vs average "apparent THC-COOH concentration" (ng/mL) at different cutoff levels 



Assay cutoff b 


15 


18 


20 


22 


25 


30 


37.5 


40 


45 


50 


55 


62.5 


60 


75 


80 


90 


100 


125 


135 


150 180 


EMIT-lOO 


12 














36 


36 


41 








62 




74 


95 


110 




153 192 


EMIT-50' 










30 


33 


39 


42 


42 


45 


48 






65 








130 




163 179 


EMIT-20 C 


16 


18 




20 


21 


24 










51 




















FPW 










21 






34 




45 






54 




78 




98 




135 




KIMS II- 










































100/50/20 e 


16 




20 




23 




39 






49 




69 




79 






96 


140 







"Average THC-COOH concentration reported in the packiage inserts for either "accuracy by recovery" or "impression studies" of the immunoassay 
products. The "nominal THC-COOH concentration" is the amount of THC-COOH compound spiked for running the immunoassays and the "apparent THC- 
COOH concentration" is the average result obtained from the immunoassays. 

'The products are indicated the "immunoassay technology-cutoff level;" the information is not shown on CEDIA package inserts. 

'Package inserts of Emit II Plus Cannabinoids assay, Dade Behring, Inc., June 2001 . Three cutoff levels: 1 00, 50, and 20 ng/mL. 

''Package inserts of AxSYM Cannabinoids assay, Abbott Laboratories, 1997. 

'Package inserts on ONLINE DAT Cannabinoids II assay, Roche Diagnositcs, 2003. The assays were run at three concentrations for each of the three 
cutoff levels: 100, 50, and 20 ng/mL. 



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Recently, Skopp and colleagues (84,85) published several studies investigating 
the stability of free and glucuronidated THC metabolites in plasma and authentic urine 
specimens. Formation of free THC-COOH increased with increasing storage tempera- 
ture in both plasma and urine. In urine samples, THC-COOH exists primarily as the 
glucuronide, and free THC-COOH is present in minute amounts. During storage, THC- 
COOH was liberated from its glucuronide in a time- and temperature-dependent man- 
ner (84). The authors reported that the dynamic change in the breakdown of the 
glucuronide is of considerable importance for the broad and highly variable changes 
observed during storage of authentic samples. The authors also investigated the stabil- 
ity of cannabinoids in hair samples exposed to sunlight ( 135). The stability of THC in 
oral fluid is also an issue of concern, although commercially available collection devices 
generally contain preservative chemicals. In the near future, it is expected that more 
studies will be carried out to investigate the stability of cannabinoids in various alter- 
native specimens. 

3.5.5. Hemp Seed/Oil Products, Synthetic THC Medication, 
and Drug Testing 

The question of whether the consumption of cannabinoid-containing foodstuffs 
or cannabinoid-based therapeutics could be used to justify the presence of urinary 
THC-COOH has been extensively investigated and reported in the literature 
(70,1 10,136-144). A number of studies in 1997 clearly showed that ingestion of what 
were commercially available hemp seed oils could produce positive cannabinoid 
immunoassay results for several days (137-140). These screen-positive specimens 
were shown to contain THC-COOH by GC/MS in most of the studies (137-139). 
Later studies indicated that there has been a significant reduction in the THC concen- 
tration of hemp food products. These studies observed only occasional screen-posi- 
tive samples and showed decreased levels of urinary THC-COOH with shortened 
detection time (141,142). In addition, the Drug Enforcement Agency (DEA) and Jus- 
tice Department added an interpretive rule to 21 CFR Part 1308. DEA interprets the 
Controlled Substances Act and DEA regulations to declare any product that contains 
any amount of THC to be a schedule I controlled substance, even if such product is 
made from portions of the Cannabis plant that are excluded from the Controlled Sub- 
stances Act definition of "marihuana' ' ( 145). However, a number of sources still exist 
globally that may provide hemp oils with considerable THC concentration. 

Oral ingestion of prescribed synthetic THC medication (dronabinol [Marinol®]) 
can also produce positive results for cannabinoid testing. Immunoassays alone cannot 
determine if a positive result could be solely a result of the use of synthetic THC. 
Importantly, ElSohly et al. (140,141) demonstrated that A 9 -tetrahydrocannabivarin 
(THCV), the C3 homolog of A 9 -THC, is a marker for the ingestion of marijuana or a 
related product. THCV is a natural product that exists only in Cannabis plants with 
THC. Thus, the detection of THCV-COOH in plasma and urine specimens would 
indicate the use or ingestion of cannabis-related products and would not support claims 
of the sole use of Marinol (143,144). 

Recently, Gustafson et al. (70) studied urinary pharmacokinetics of THC-COOH 
after controlled clinical study of multiple-dose oral THC administration. Varying THC 



Immunoassays to Detect Cannabis Abuse 



167 



doses were administered through gelatin capsule and liquid hemp oil, along with THC 
in sesame oil, to examine effects of dose, vehicle type, and form. The maximum THC- 
COOH concentration ranges in urine samples were 7.3-38.2, 5.4-31, 26-436, and 19- 
264 ng/mL for THC daily doses of 0.39, 0.47, 7.5, and 14.8 mg, respectively. Following 
the administration of these daily THC doses, the mean urinary terminal elimination 
half-lives averaged 50.3 ± 17.4, 44.2 ± 19.4, 64.0 ± 22.5, and 52.1 ± 21.8 hours, 
respectively. 

3.5.6. Cannabinoid-to-Creatinine Ratio Studies 

Regardless of the cutoff levels chosen for cannabinoids testing, substantial vari- 
abilities have been observed between subjects and between doses in the excretion 
profiles of THC-COOH. Huestis et al. (67) demonstrated that mean detection times in 
urine following smoking varied considerably between individuals even in highly con- 
trolled smoking studies. It has been documented that consecutive urine specimens 
may fluctuate below and above the cutoff during the terminal elimination phase when 
THC-COOH concentrations approach the cutoff (67,71). The normalization of drug 
excretion to urine creatinine concentration has been well documented not only to pre- 
dict new drug use but also to reduce the variability of drug measurements attributable 
to urine dilution ( 146-150). Gustafson et al. (70) observed an up to fourfold intrasubject 
variation across doses and a sixfold intersubject variation for a single dose in terminal 
elimination half-lives. However, the authors found no significant effect of creatinine 
normalization on pharmacokinetic parameters, half-life, maximum excretion rate, and 
time to maximum excretion rate following oral THC administration. The authors also 
showed that the apparent urinary elimination half-life of THC-COOH prior to reach- 
ing 15 ng/mL concentration was significantly shorter than the terminal urinary elimi- 
nation half-life. 

3.5.7. Specimen Validity Testing 

The normalization of THC metabolite concentration to urine creatinine concen- 
tration has been proven to help address the issue of fluctuating THC-COOH concen- 
tration as a result of specimen donor hydration status. In addition to physiological 
fluctuation, intentional dilution of urine specimens in vivo or in vitro may lower the 
levels of drug below the threshold for a positive screen result and thus avoid further 
testing (151-154). Moreover, attempts to conceal drug abuse by water dilution are 
most likely to play a substantial role when concentrations are at or near the detection 
threshold, such as the terminal stages of drug eliminations (151-153). 

Frazer et al. ( 151 ) showed that cannabinoids were among the most often con- 
firmed drug classes in diluted specimens. The authors recommended the reduction of 
the FN rate for DAT by incorporating lower screening and confirmation cutoff levels 
for diluted specimens that screened negative using the SAMHSA mandated cutoff 
concentrations. Nevertheless, the more direct approach is to test the samples for signs 
of dilution or substitution. Cook et al. ( 154) extensively reviewed the published scien- 
tific literature for the characterization of human urine for specimen validity determi- 
nation in workplace drug testing. The authors developed criteria for classifying 
submitted urine as substituted, and the criteria were then validated by controlled dehy- 
dration study (154,155). 



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Deliberate invalidation of the specimen by chemical adulteration has also been 
applied to mask urine screening (156-160). Among the drugs of abuse assays, can- 
nabinoid testing is the most sensitive to chemical additives, especially to oxidizing 
agents, as adulterants that may negatively affect the target analyte for drug testing. 
Tsai et al. ( 158) investigated the interaction of various oxidizing agents with the THC 
metabolites under a number of sample matrix conditions and observed a spectrum of 
manifestations with regard to their effects on immunoassays and GC/MS analysis. 
Paul and Jacobs (160) evaluated different oxidizing adulterants. Several oxidizing 
adulterants that are difficult to test by conventional urine adulterant testing methods 
showed considerable effects on the destruction of THC-COOH. The time and tem- 
perature for these effects were similar to those used by most laboratories to collect and 
test specimens, and the loss of THC-COOH was significant (>94%) in several cases. 

In response to the specimen validity issues, SAMHSA and the Department of 
Transportation initiated the process to develop standards for testing and reporting of 
sample adulteration, substitution, and dilution (66 FR 43876). The revised mandatory 
Guidelines for specimen validity testing were published in 2004 (92). Many immu- 
noassay manufacturers also offer products or utility channels for specimen validity 
testing. Alternative matrices are generally perceived as less vulnerable to adulteration 
if the sample collection procedures are directly observed. However, there are environ- 
mental contamination and bias concerns for some of the matrices. The scenarios of 
passive exposure to marijuana smoking are also being investigated for hair, sweat, and 
oral fluid testing. The World Wide Web distributors of adulteration products for urine 
testing have been offering an array of adulteration products for hair and saliva /oral 
fluid testing. The proposed SAMHSA Guidelines provide specific information and 
requirements on conducting specimen validity testing for all alternative specimens 
submitted for mandatory drug testing programs (91). 

4. Conclusions 

The application of cannabinoid immunoassays as the initial test remains the most 
economic and efficient screening tool "to eliminate negative specimens from further 
consideration" and "to identify the class of drugs that requires confirmatory test" (90,91 ). 
The regulated cutoff levels provide a uniform approach for the mandated drug-testing 
programs. On the other hand, the availability of multiple cutoff choices from the immu- 
noassay kits provides alternative means for certain drug-testing programs that require 
the use of cutoff levels different from regulated workplace drug testing. 

Although results from urine drug testing alone are not sufficient to answer many 
demanding forensic and clinical questions, the detection and quantification of urinary 
cannabinoids have not only provided insights on cannabinoid metabolism but also played 
a pivotal role in overall drug-testing programs. A number of immunoassays have been 
developed or adapted for detecting cannabis abuse using various biological fluids and 
forensic matrices. The technical challenges for detecting cannabinoids in other biologi- 
cal matrices are higher as compared to urinalysis, and more research and development 
are currently ongoing in diverse fields relating to alternative specimen testing. 

Regardless of the specimen type tested, it is highly recommended that presump- 
tive positive results be confirmed to rule out issues of cross-reactivity with 



Immunoassays to Detect Cannabis Abuse 



169 



noncannabinoid compounds. The complexity of cannabinoid chemistry and pharma- 
cokinetics has challenged the development of immunoassays to meet the diverse goals 
of detecting or deterring cannabis abuse. However, various strategies have been 
extensively explored for manipulating the antibody selectivity and immunoassay sen- 
sitivity and specificity. Naturally, the results for testing one specimen with different 
immunoassay technologies or platforms can vary to some extent because of the differ- 
ent antibodies and reagent systems used. 

Because of the interindividual differences in metabolism, specimens that show 
the same apparent THC-COOH concentration as determined by an immunoassay can 
produce different THC-COOH concentrations as determined by GC/MS analysis. This 
is generally not a real issue for routine drug testing when the majority are either truly 
"drug-free" negative specimens (e.g., workplace testing) or high drug concentration 
positive specimens (e.g., criminal justice testing). For detecting clinical samples that 
contain cannabinoid immunoassay results between the screen cutoff and confirmation 
cutoff, a more specific assay may not have adequate sensitivity, whereas a more sen- 
sitive immunoassay may have a higher percentage of unconfirmed positives. A higher 
confirmation rate does confer efficiency and economical advantage for the process 
that involves large volume drug screening. 

Although immunoassays lack the defined specificity of GC/MS, they remain the 
only practical means of conducting large- volume screening programs. For routine 
workplace drug testing, immunoassays work well in terms of eliminating the bulk of 
drug-free samples from further testing. Immunoassays are relatively easy to perform 
and do not require sample pretreatment for urinalysis. The values and utilities of these 
immunoassays have been supported by the hundreds of millions of samples tested 
over the past decades. In addition to qualitative screening, the assays can be run in 
semi-quantitative mode to provide an approximate correlation with GC/MS value and 
to aid in the estimation of dilution factor needed for conducting GC/MS confirmation. 

In conclusion, the key factors that impact the design and performance of cannab- 
inoids immunoassays may include (1) the chemical characteristics and pharmacoki- 
netics of cannabinoids, (2) the analytical performance characteristics of the initial and 
confirmation testing for the sample matrix of interest, (3) the regulatory requirements 
and cutoff choices for both initial screening and confirmatory tests, (4) the analyte 
stability and validity of the testing specimen, (5) potential interference from structur- 
ally related compounds, and (6) the goals of drug-testing programs or the relevance to 
clinical decisions. The understanding of these factors, together with knowledge of the 
analytical screening and confirmation techniques for drug testing, are imperative for 
the appropriate interpretation of the drug-testing results. 

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89. Patent families for cannabinoids immunoassays (Hoffman La Roche / Roche Diagnos- 
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96. AGSA Swiss Working Group for Drugs of Abuse Testing Guidelines. (2003)(http:// 
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98. EWDTS (European Workplace Drug Testing Society) Laboratory Guidelines. (2002) 
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99. Ferrara, S. D., Tedeschi, L., Frison, G., et al. (1994) Drugs-of-abuse testing in urine: 
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116. Spiehler, V. (2004) Comment on "An evaluation of rapid point-of-collection oral fluid 
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118. Jurado, C. and Sachs, H. (2003) Proficiency test for the analysis of hair for drugs of 
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120. Wolff, K., Farrell, M., Marsden, J., et al. (1999) A review of biological indicators of 
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123. Armbruster, D. A., Tillman, M. D., and Hubbs, L. M. (1994) Limit of detection (LQD)/ 
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124. Goldberger, B. A. and Cone, E. J. (1994) Confirmatory tests for drugs in the workplace 
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125. Wu, A. H. (1995) Mechanism of interferences for gas chromatography/mass spectrom- 
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126. Underwood, P. J., Kananen, G. E., and Armitage, E. K. (1997) A practical approach to 
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127. Lehrer, M. (1998) The role of gas chromatography/mass spectrometry. Instrumental tech- 
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128. Haver, V. M., Romson, J. L., and Sadrzadeh, S. M. (1991) Semiquantitation of cannabinoid 
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129. Blanc, J. A., Manneh, V. A., Ernst, R., et al. (1993) Adsorption losses from urine-based 
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130. Paul, B. D., McKinley, R. M., Walsh, J. K. Jr, Jamir, T. S., and Past, M. R. (1993) Effect 
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131. Romberg, R. W. and Past, M. R. (1994) Reanalysis of forensic urine specimens contain- 
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132. Dugan, S., Bogema, S., Schwartz, R. W., and Lappas, N. T. (1994) Stability of drugs of 
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133. Roth, K. D., Siegel, N. A., Johnson, R. W., Jr., et al. (1996) Investigation of the effects of 
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134. Moody, D. E., Monti, K. M., and Spanbauer, A. C. (1999) Long-term stability of abused 
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135. Skopp, G., Potsch, L., and Mauden, M. (2000) Stability of cannabinoids in hair samples 
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136. Cone, E. J., Johnson, R. E., Paul, B. D., Mell, L. D., and Mitchell, J. (1988) Marijuana- 
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137. Costantino, A., Schwartz, R. H., and Kaplan, P. (1997) Hemp oil ingestion causes posi- 
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139. Lehmann, T., Sager, F., and Brenneisen, R. (1997) Excretion of cannabinoids in urine 
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140. Fortner, N., Fogerson, R., Lindman, D., Iversen, T., and Armbruster, D. (1997) A mari- 
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141. Bosy, T. Z. and Cole, K. A. (2000) Consumption and quantitation of delta9- tetrahydro- 
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142. Leson, G., Pless, P., Grotenhermen, F., Kalant, H., and ElSohly, M. A. (2001) Evaluating 
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143. ElSohly, M. A., deWit, H., Wachtel, S. R., Feng, S., and Murphy, T. P. (2001) Delta9- 
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144. ElSohly, M. A., Feng, S., Murphy, T. P., et al. (2001) Identification and quantitation of 
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146. Huestis, M. A. and Cone, E. J. (1998) Differentiating new marijuana use from residual 
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149. Fraser, A. D. and Worth, D. (2002) Monitoring urinary excretion of cannabinoids by 
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150. Fraser, A. D. and Worth, D. (2003) Urinary excretion profiles of 1 l-nor-9-carboxy-delta9- 
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Int. 133, 26-31. 

151. Fraser, A. D. and Zamecnik, J. (2003) Impact of lowering the screening and confirmation 
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152. Cone, E. J., Lange, R., and Darwin, W. D. (1998) In vivo adulteration: excess fluid inges- 
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156. Wong, R. (2002) The effect of adulterants on urine screen for drugs of abuse: detection 
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Chapter 8 



Mass Spectrometric Methods 

for Determination of Cannabinoids 

in Physiological Specimens 

Rodger L. Foltz 

1. Introduction 

This chapter describes the published mass spectrometric (MS) methods that have 
proven most effective for quantitative measurement of A'-tetrahydrocannabinol (THC) 
and its major metabolites in physiological specimens. Because determination of 11- 
nor-9-carboxy- A'-tetrahydrocannabinol (THCA) in urine continues to be the most fre- 
quently used indicator of marijuana use, the first portion of the chapter will discuss 
methods for measurement of THCA in urine. However, the major portion of the chap- 
ter is devoted to the most recent developments for measuring THC and its metabolites 
in other biological specimens including blood, plasma, meconium, oral fluids, hair, 
and other tissues. Tables 1-7 are designed to facilitate location of references describ- 
ing analytical methods involving key components for analysis of cannabinoids in vari- 
ous matrices. 

Analysis of THC and its metabolites in biological specimens has been reviewed 
by Lindgren (1), Foltz (2), Bronner and Xu (3), Goldberger and Cone (4), Cody and 
Foltz (5), and Staub (6). 

The selection of internal standards is an important factor in the development of 
quantitative assays involving MS. Because of the demand for effective internal stan- 
dards for MS analysis of THC and its major metabolites, a variety of deuterium-labeled 
analogs have become commercially available. THC-d 3 , THCA-d 3 and trideuterated 
1 1 -hydroxy- A 9 -tetrahydrocannabinol (HO-THC-d 3 ) have often been used as internal 

From: Forensic Science and Medicine: Marijuana and the Cannabinoids 
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey 

179 



180 



Foltz 



standards. However, cannabinoid analogs with more than three deuteriums (THC-d 6 , 
THC-d„ THCA-d 6 , THCA-d„ THCA-d 10 , and HO-THC-d 6 ) are reported to be even 
more effective as internal standards (7-10). 

2. Determination of THCA in Urine 

THCA is primarily excreted in urine as the ester-linked glucuronide conjugate. 
Consequently, the urine is most often subjected to mild alkaline hydrolysis to release 
the THCA ( 11,12). Enzymatic hydrolysis using (3-glucuronidase can also free the THCA 
from the conjugate, but the procedure takes considerably longer than alkaline hydrolysis 
(13,14). After hydrolysis the urine is acidified and extracted by either liquid/liquid or 
solid-phase extraction (SPE). A solvent mixture of hexane and ethyl acetate, typically 
7: 1 (v/v), has been used most often for extraction of free THCA in urine (11). A wide 
variety of solid-phase systems are also available for extraction of THCA in urine (10,15- 
24), and two research groups have selectively extracted THCA from urine by means 
of immobilized antibodies (8,25). 

THCA has two polar functional groups that must be derivatized prior to gas chro- 
matography (GC)/MS analysis. The carboxyl group and the phenolic group can both 
be derivatized by trimethylsilylation or by methylation. Trimethylsilylation is most 
often performed by adding to-(trimethylsilyl)-trifluoroacetamide (BSTFA) with 1% 
trimethylchlorosilane (TMCS) to the dried extract and heating at approx 70°C for 20 
minutes, followed by direct injection into the GC/MS system (17,18). Methylation is 
generally performed by addition of methyl iodide in the presence of tetramethylam- 
monium hydroxide (TMAH) in dimethyl sulfoxide (16,26). Some investigators have 
used propyl iodide when interference problems were encountered after derivatizing 
with methyl iodide (27); others have used a perfluorinated anhydride and a 
perfluorinated alcohol (10,24,28,29). The latter protocol can provide increased sensi- 
tivity, particularly when the derivatives are detected by negative ion chemical ioniza- 
tion mass spectrometry (GC/NCTMS; ref. 28). However, it is important to remove the 
perfluorinated anhydride reagent by evaporation prior to reconstitution and injection 
into the GC/MS because the anhydride tends to degrade the chromatographic column. 

Szirmai and co-workers compared five different methods for derivatization of 
THCA and two other acidic metabolites of THC in urine (9). Two of the methods 
involved esterification of the carboxylic acid group with diazomethane followed by 
trimethylsilyation or trifluoroacetylation of the phenolic group; the other three meth- 
ods employed (1) BSTFA alone, (2) methyl iodide-TMAH, or (3) pentafluoropropionic 
anhydride (PFPA) and trifluoroethanol. 

Nearly all GC/MS assays for determination of THCA in urine employ fused silica 
capillary columns with methyl silicone or 5% phenylmethylsilicone stationary phases. 
Electron ionization (EI) continues to be the dominant method for ionizing derivatized 
THCA. With EI-MS, each of the reported THCA derivatives yields at least three ions 
with high relative intensities, an important benefit in forensic analyses. 

The first published liquid chromatography (LC)/MS assay for determination of 
THCA in urine employed positive ion electrospray ionization (ESI; ref. 30). Under 
selected ion monitoring the protonated molecule ion (M + H) + at m/z 345 was domi- 
nant and could be detected down to 2.5 ng/mL. Up-front collision-induced dissocia- 



MS for Detection of Cannabinoids 



181 



tion generated qualifying ions at m/z. 327 and 299, but their ion intensities were rela- 
tively low and thereby increased the lower limit of detection to 15 ng/mL. Signifi- 
cantly better sensitivity has been achieved by monitoring the (M - H)~ ions for THCA 
(m/z. 343) and THCA-d 3 (m/z 346) formed by ESI (23). 

Weinmann and co-investigators (21) developed a very rapid LC/MS/MS assay 
for THCA in urine using negative ion atmospheric pressure chemical ionization (APCI) 
in combination with selected-reaction monitoring. When subjected to collision-induced 
dissociation, the (M - H) ion at m/z 343 fragmented to abundant ions at m/z 325, 299, 
and 245. The runtime took 6 minutes, and the lower limit of quantitation was 5 ng/mL. 
Investigators in the same laboratory reported using positive-ion turboionspray to 
determine THCA and THCA glucuronide in urine by LC/MS/MS (31). 

Skopp and Potsch used LC/MS/MS to study the stability of THCA and THCA- 
glucuronide in urine and plasma stored at temperatures of -20, 4, 20, and 40°C (32). 
The analytes and their deuterated internal standards were ionized by turboionspray, 
and the protonated molecule ions collisionally dissociated to abundant product ions. 

Unfortunately, THCA and other cannabinoids are not as efficiently ionized by 
either ESI or APCI as most other drugs. Nevertheless, the advantage of not having to 
derivatize an analyte prior to analysis is an inducement to utilize LC/MS rather than 
GC/MS. 

Potential problems that can occur in determination of THCA in urine include 
interferences (27,33), adsorptive losses during storage and extraction (12,29,34-36), 
and degradation of THCA as a result of adulteration of a urine sample (37). 

3. Determination of Other Cannabinoids in Urine 

Although detection of THCA in urine continues to be the primary method for 
identifying recent use of marijuana, Manno and Manno and their co-investigators have 
shown that THC and other metabolites of THC are also excreted in urine as glucu- 
ronide conjugates that are not, however, as easily hydrolyzed as THCA glucuronide 
(38,39). THC and its hydroxylated metabolites are excreted in urine primarily as ether- 
linked glucuronide conjugates that do not undergo hydrolysis under alkaline condi- 
tions. Enzymatic hydrolysis using (3-glucuronidase from Escherichia coli at a pH of 
6.8 is highly effective in cleaving ether-linked glucuronide conjugates. Manno et al. 
have used this method for quantitative analysis of cannabidiol, cannabinol, THC, and 
six THC metabolites in plasma and urine. After enzymatic hydrolysis, they extracted 
the cannabinoids with hexane:ethyl acetate (7:1), derivatized them with BSTFA, and 
analyzed the products by electron ionization GC/MS. Analysis of urine samples by 
this method proved useful for estimating the time of marijuana use ( 14). 

GC/MS analysis for 1 l-nor-A 9 -tetrahydrocannabivarin-9-carboxylic acid 
(THCVA) has been used to determine whether the presence of THCA in a subject's 
urine indicates the use of marijuana or is solely the result of the use of the prescription 
drug Marinol® (synthetic THC; ref . 40). A 9 -Tetrahydrocannabivarin, a homolog of THC, 
is present in most marijuana and is metabolized in the body to THCVA (41 ). Because 
THCVA is a homolog of THCA, the two compounds behave very similarly during 
extraction and derivatization but have different retention times and form abundant 
ions that differ by 28 amu (40). 



182 



Foltz 



4. Determination of Cannabinoids in Blood or Plasma 

Cannabinoid concentrations in urine are not very useful for determining impair- 
ment or recent use of marijuana. Therefore, in forensic cases it is important to mea- 
sure cannabinoid concentrations in blood or plasma, particularly the concentrations of 
THC and HO-THC, the two psychoactive cannabinoids. However, analysis of can- 
nabinoids in blood or plasma is complicated by the difficulty of separating the can- 
nabinoids from the abundance of endogenous lipophilic and proteinaceous compounds 
in blood that are not generally present in urine. Furthermore, concentrations of THC 
and HO-THC in blood decrease rapidly after smoking marijuana or after oral inges- 
tion of cannabinoids. 

Most published methods for determination of cannabinoids in blood or plasma 
have not included enzymatic hydrolysis of glucuronide conjugates. However, recent 
studies have shown that significant but variable proportions of THC, HO-THC, and 
THCA are present in plasma as glucuronide conjugates (42). Hydrolysis of the glucu- 
ronide conjugates is most effectively achieved using (3-glucuronidase from E. colt 
(14,42). 

Liquid/liquid extractions have been used to separate cannabinoids from blood or 
plasma (38,43^5). When Chu and Drummer evaluated eight different buffers and ten 
different solvents for extracting THC from whole blood, they obtained the best results 
by adding 1 mL of 1 M ammonium sulfate to 1 mL of blood and extraction with 7 mL 
of hexane (45). However, because SPE is capable of achieving better selectivity, it is 
now more widely used for extraction of cannabinoids from blood and plasma. 

D'Asaro evaluated an automated SPE system (Zymark RapidTrace™) for de- 
termining THC and THCA in whole blood (46). THC-d 3 and THCA-d 3 were added 
to 1 mL of warm blood followed by addition of 3 mL of acetonitrile containing 10% 
acetone. After vortexing and centrifugation the supernatant was separated and con- 
centrated by evaporation, then acidified with 0. 1 M HC1 and subjected to SPE. Vari- 
ous SPE cartridges were evaluated; the C-8 anion exchange copolymer sorbent provided 
the best overall recoveries and the cleanest extracts. THC and THCA were eluted at 
the same time and then derivatized with BSTFA and analyzed by GC/MS with elec- 
tron ionization and selected-ion monitoring. The lower limits of quantitation (LOQs) 
were 2.0 ng/mL for THC and 1.0 ng/mL for THCA. 

The combination of a liquid/liquid extraction followed by a SPE was employed 
by Felgate and Dinan for analysis of THC and THCA in whole blood (47). After 
addition of deuterated internal standards to 0.5 mL of blood diluted with 1.0 mL of 
water and 1 mL of 1.0 phosphate buffer (pH 4.0), the diluted blood was extracted with 
hexane/ethyl acetate (5:1). The extract was evaporated to dryness, reconstituted with 
hexane, and further cleaned up by SPE using Varian Bond Elut THC cartridges. THC 
was eluted with hexane containing 50% toluene, and the THCA was eluted separately 
with hexane containing 40% ethyl acetate. The THC and THCA extracts were ana- 
lyzed separately after each was derivatized with pentafluoropropanol and 
pentafluoropropionic anhydride. If the derivatized THC and THCA extracts were com- 
bined, sensitivity was reduced due to interferences. The GC/MS analysis, with elec- 
tron ionization and selected-ion monitoring, achieved an LOQ of 1 ng/mL for each 
analyte. 



MS for Detection of Cannabinoids 



183 



A fully validated GC/MS assay for determination of THC, HO-THC, and THCA 
in serum was recently reported by Steinmeyer et al. (48). Deuterated internal stan- 
dards for each analyte were added to 1 mL of serum along with 0.2 mL ethanol and 
2 mL 0.1 M phosphate buffer (pH 9.0). Samples were extracted on CI 8 bonded-phase 
adsorption cartridges. The analytes were eluted from the cartridges with acetone/metha- 
nol (1:1), and the extracts were evaporated to dryness and derivatized with 
tetrabutylammonium hydroxide, dimethylsulfoxide, and iodomethane. The derivatized 
extracts were acidified with 0. 1 M HC1, extracted into isooctane, and analyzed by EI- 
GC/MS in the selected-ion monitoring mode. The LOQs in ng/mL were 0.62 (THC), 
0.68 (HO-THC), and 3.35 (THCA). The method was cross-validated for analysis of 
liver microsomal preparations. 

A method for measurement of THC and THCA in plasma was developed at the 
Center for Human Toxicology, University of Utah, to analyze specimens from clinical 
studies (49). After addition of deuterated internal standards to 1 mL of plasma, 1 mL 
of acetonitrile was added and the samples were vortexed and centrifuged. The super- 
natant was separated and combined with 4 mL of 0.1 M acetate buffer (pH 7.0) and 
poured onto a conditioned CleanScreen ZSTHC020 SPE column. The column was 
then washed with 0. 1 M acetate buffer and dried under vacuum. THC was eluted with 
hexane/ethyl acetate/ammonia hydroxide (93:5:2), and the THCA was eluted sepa- 
rately with hexane/ethyl acetate (70:30). The eluants containing THC and THCA were 
combined, evaporated to dryness, and derivatized with hexafluoroisopropanol (HFIP) 
and trifluoroacetic anhydride (TFAA). GC/MS analysis with negative ion chemical 
ionization gave abundant molecular anions for the derivatized THC (m/z 410) and 
abundant fragment ions (m/z 422) formed by loss of (CF 3 ) 2 CHOH from the molecular 
anion of derivatized THCA. LOQs were 0.5 ng/mL (THC) and 2.5 ng/mL (THCA). 

Huestis et al. developed and fully validated a GC/MS assay for simultaneous 
determination of THC, HO-THC, and THCA in human plasma (42). Their method 
includes enzymatic hydrolysis of glucuronide conjugates, simultaneous SPE of all 
three analytes in a single eluant, derivatization with BSTFA, and analysis by positive 
ion chemical ionization GC/MS. Ions were monitored for each analyte and internal 
standard: THC, m/z 387; THC-d 3 , m/z 390; HO-THC, m/z. 459; HO-THC-d 3 , m/z 462; 
THCA, m/z 489; and THCA-d 3 , m/z 492. Enzymatic hydrolysis with E. coli (3-glucu- 
ronidase resulted in significantly higher concentrations of HO-THC and THCA in the 
eluants than could be obtained without the hydrolysis step. Extraction recoveries ranged 
from 67.3 to 83.5% for all three analytes. LOQs were 0.5 ng/mL for THC and HO- 
THC and 1.0 ng/mL for THCA. 

Another method developed for analysis of clinical samples employed gas chro- 
matography/tandem mass spectrometry (GC/MS/MS; ref. 50). Deuterated internal stan- 
dards for THC and HO-THC were added to a 2-mL aliquot of human plasma followed 
by 2 mL of acetonitrile and 2 mL of 0.1 M phosphate buffer (pH 6.0). After vortexing 
and centrifugation, the supernatant was transferred to a conditioned Bond Elut Cer- 
tify- 1 extraction column. After several washing steps the THC and HO-THC were 
eluted from the column with methylene chloride, derivatized by trimethylsilylation, 
and analyzed by GC/MS/MS using positive ion chemical ionization with ammonia as 
the reagent gas. The protonated molecule ions for trimethylsilylated THC (m/z 387) 



184 



Foltz 



and HO-THC (m/z 475) were collisionally dissociated to product ions at m/z 293 and 
detected by selected-reaction monitoring. LOQs were 50 pg/mL for THC and 100 pg/ 
mL for HO-THC. 

Several preliminary efforts to measure cannabinoids in blood or plasma by LC/ 
MS have been reported. Hughes et al. compared ESI, APCI, and atmospheric-pressure 
photoionization (APPI) for analysis of THC, THCA, and HO-THC in blood. APCI 
was more sensitive than ESI. THCA and HO-THC had better sensitivity in the nega- 
tive ionization mode, while THC showed better sensitivity in the positive ionization 
mode. APPI was three to five times more sensitive for all three cannabinoids (51). 
After SPE of THC, HO-THC, and THCA in blood, Mireault analyzed the extracts 
using an ion trap LC/MS (Finnigan LCQ) operated in the APCI mode. THC was detected 
using MS/MS, but HO-THC and THCA required MS/MS/MS to achieve adequate 
selectivity (52). 

5. Determination of Cannabinoids in Adipose Tissue 
and Other Tissues 

Quantitative determination of cannabinoids in adipose tissue is even more chal- 
lenging than analysis of cannabinoids in blood. Johansson et al. developed a lengthy 
assay for measurement of THC in human fatty tissue (53). The procedure included 
homogenization of the fat samples with hexane:isopropanol (3:2) and sequential SPEs 
with Lipidex 5000 gel and a CI 8 resin. The extracted THC was derivatized with N- 
methyl-/V-(f-butyldimethylsilyl)trifluoroacetamide (MTBSTFA), and the derivatized 
THC was purified by preparative HPLC using a CI 8 column. Finally, the purified and 
derivatized THC was analyzed by means of GC and high-resolution MS. 

Investigators in the Department of Forensic Medicine at Kyushu University, Japan, 
developed a relatively simple method for determination of THC in human tissues in- 
cluding brain, lung, kidney, muscle, liver, spleen, and adipose tissue (54). Tissue 
samples (0.1 g of fat or 0.5 g of the other tissues) were homogenized with 3 mL of 
acetonitrile. After centrifugation, the supernatant was concentrated by evaporation 
and mixed with 2 mL of 0.2 M sodium hydroxide. The aqueous solution was extracted 
with 3 mL of hexane: ethyl acetate (9:1); the organic extract was washed with 2 mL of 
0. 1 M HC1 to remove basic compounds and then evaporated to dryness for derivatization 
in a solution of iodomethane, tetrabutylammonium hydroxide, and dimethyl-sulfox- 
ide. Derivatized extracts were analyzed by GC/MS using electron ionization and 
selected-ion monitoring. The lower limit of detection for THC in each of the tissues 
examined was 1 ng/g. 

6. Determination of Cannabinoids in Meconium 

Clinicians are increasingly interested in determining when a newborn infant has 
been prenatally exposed to marijuana or other drugs of abuse. Meconium is the pre- 
ferred matrix for analysis in these cases because it retains drugs and drug metabolites 
for a longer time than does an infant's blood or urine (55). 

GC/MS confirmation of THCA in meconium was first reported by Moore et al. 
(56). The meconium was initially screened by fluorescence polarization immunoassay 



MS for Detection of Cannabinoids 



185 



(Abbott Laboratories, Abbott Park, IL). Positives were then analyzed by GC/MS. After 
homogenization in methanol, THCA-d 3 was added along with 11.8 M potassium 
hydroxide, and the mixture was allowed to stand for 15 minutes. After centrifugation 
the aqueous supernatant was diluted with deionized water and extracted with 
hexane:ethyl acetate (9:1) to remove lipophilic nonacidic compounds; the aqueous 
layer was acidified with 0.1 NHCl and extracted with hexane: ethyl acetate (9:1). The 
resulting organic layer was evaporated to dryness and derivatized with MTBSTFA. 
EI-GC/MS analysis monitored ions at m/z 572, 515, and 413 for THCA and m/z 575, 
518, and 416 for THCA-d 3 . The lower limit of detection (LOD) for THCA was 2 ng/g. 

ElSohly and co-investigators extensively investigated methods of measuring THC 
and its metabolites in meconium (8,55). They found that HO-THC and 8(3,1 1-diHO- 
THC were present in significant quantities in meconium from neonates whose moth- 
ers had used marijuana and that those metabolites were mainly in the form of 
glucuronide conjugates. The investigators developed two different GC/MS assays for 
determination of cannabinoids in meconium; both included enzyme hydrolysis, but 
one employed liquid/liquid extraction (55) and the other an immunoaffinity extraction 
procedure (8). The liquid/liquid extraction method included the following procedures: 
after addition of THC-d, and THCA-d 6 the meconium was homogenized in methanol 
and centrifuged, and the supernatant was evaporated to dryness. The residue was taken 
up in saturated monobasic potassium phosphate and extracted with chloroform. The 
chloroform extract was evaporated to dryness and the residue dissolved in 0.1 M phos- 
phate buffer (pH 6.8) containing (3-glucuronidase (E. coli, Type IX-A). After 16 hours 
at 37°C, the sample was cooled, acidified with 1 Af HQ, and extracted with hexane:ethyl 
acetate (9:1). Acidic cannabinoids were removed from the organic solution by extrac- 
tion into 1 N sodium hydroxide, reacidified, and extracted back into hexane:ethyl acetate 
before derivatization with BSTFA. Neutral cannabinoids remaining in the original 
hexane:ethyl acetate solution were subjected to further clean-up prior to derivatization 
with pyridine and acetic anhydride. The neutral and acidic cannabinoids were ana- 
lyzed separately by GC/MS. The LODs for the THC metabolites ranged from 2 to 15 ng/g. 
Surprisingly, 8(3,1 1-diOH-THC was found in the acidic fraction, along with THCA. 

The second method, employing an immunoaffinity extraction, proved to be much 
faster and more selective than the liquid/liquid extraction method. The immunoaffinity 
resin was prepared by immobilization of THC antibody (Roche Diagnostic Systems, 
Somerviile, NJ) onto cyanogen bromide-activated Sepharose 4B, and stored in 1 M 
NaCl solution containing 0.05% NaN 3 . After addition of deuterated internal standards 
and 3 mL of methanol, the meconium (0.5 g) was homogenized and centrifuged and 
the supernatant was evaporated to dryness. The dried residue was extracted with 2 mL 
of isopropanohwater (95:5), and after centrifugation the supernatant was again sepa- 
rated and evaporated to dryness. The residue was taken up in 2 mL of 0. 1 M phosphate 
buffer (pH 6.8) and hydrolyzed with (3-glucuronidase (E. coli, type IX-A). The 
immunoaffinity-resin slurry was added to the hydrolyzed sample and poured into a frit 
filter cartridge and the liquid allowed to pass through under a slight vacuum. The resin 
was washed once with phosphate saline buffer (pH 7.0) and three times with deion- 
ized water. After the analytes were eluted with acetone and the extract evaporated to 
dryness, they were trimethylsilylated using BSTFA and 1% TMCS and analyzed by 



186 



Foltz 



EI-GC/MS with selected ion monitoring. The LODs were 1.0 ng/g for THCA and HO- 
THC and 2.5 ng/g for 80,1 1-diHO-THC. 

Authors of the above immunoaffinity procedure reported that of 24 presumptive 
positive meconium samples analyzed, 15 were confirmed positive for THCA and 18 
were positive for HO-THC. Only three specimens were positive for 813,1 1-diHO-THC. 

7. Determination of Cannabinoids in Oral Fluids 

Analysis of oral fluids to detect recent use of drugs of abuse is of increasing 
interest because sampling is less invasive than collection of urine or blood. However, 
unlike most other drugs, THC gets into oral fluids primarily by direct deposition into 
the oral mucosa during smoking or oral ingestion, rather than being transferred from 
blood to saliva. Consequently, concentrations of metabolites of THC are very low and 
difficult to detect in this matrix. 

Niedbala et al. compared results from analysis of urine and oral fluids from sub- 
jects that smoked marijuana or ingested marijuana plant material (24). Oral fluid was 
collected using a treated absorbent cotton fiber pad affixed to a nylon stick (OraSure 
Technologies, Bethlehem, PA). After absorbing fluids in the mouth, the pad was placed 
in a preservative solution that was subsequently analyzed for THC. THC-d 3 was added 
to 200 liL of diluted oral fluid, and the specimen was treated with 2 mL of 0.2 M 
sodium hydroxide and extracted with 3 mL of hexane:ethyl acetate (9:1). The organic 
layer was washed with 3 mL of 0.1 MHO to remove basic compounds and the organic 
layer was separated and evaporated to dryness. The dried extract was derivatized with 
30 [ih of BSTFA and 30 (iL of ethyl acetate at 70°C for 30 minutes before analysis by 
GC/MS/MS using electron ionization and selected-reaction monitoring. The LOQ for 
THC in oral fluids was 0.5 ng/mL. 

When detection of THC in oral fluids was compared to detecting THCA in urine, 
the probability of a positive test in oral fluids was higher in specimens collected over 
the first 6 hours following exposure. Subsequently, positivity in urine specimens 
increased and generally exceeded that of oral fluid in specimens collected after 16 
hours (24). 

In an earlier study Menkes et al. collected oral fluids from 13 experienced users 
after each of them had smoked one marijuana cigarette. Each saliva sample (20-200 |J,L) 
was added to 200 (iL of 8 M urea and extracted with 4 mL of pentane. The organic 
extract was evaporated to dryness, derivatized with pentafluoropropionic anhydride 
and analyzed by GC/MS using electron ionization and selected-ion monitoring. Con- 
centrations of THC were compared to measurements of heart rate and intoxication 
over a period of 4 hours after smoking. The results indicated that salivary THC levels 
can be a sensitive index of recent cannabis smoking, and appear more closely linked 
with the effects of intoxication than do either blood or urine cannabinoid levels (57). 

Brodbelt and co-investigators used commercially available 30-|J,m 
poly(dimethylsiloxane) solid-phase microextraction fibers to absorb THC, cannabidiol, 
and cannabinol from saliva specimens collected after smoking (58). One mL of saliva 
was diluted with 1 mL of deionized water and 0.5 mL of acetic acid. THC-d 3 was 
added, and the solution was transferred to a vial containing the solid-phase 
microextraction fibers. The fibers were subsequently transferred to a heated (270°C) 



MS for Detection of Cannabinoids 



187 



injection port, which caused thermal desorption of the cannabinoids into the GC/MS. 
The mass spectrometer was operated in full-scan mode between 120 and 350 amu. 
The ions used for quantitation were THC (m/z. 314, 299, and 231), cannabidiol (m/z 
314 and 231), and cannabinol (m/z 310, 295, and 238). The range of quantitation for 
each cannabinoid was 5-500 ng/mL. 

8. Determination of Cannabinoids in Hair 

Determination of drugs in hair has continued to grow in importance; its advan- 
tages over analysis of other matrices are that it is relatively noninvasive, and drugs 
can be detected in hair for a much longer time period. However, cannabinoids in blood 
are not taken up in hair nearly as efficiently as most other drugs are. As a result, 
concentrations of cannabinoids in hair after smoking or ingestion of marijuana are 
very low and can only be detected with extremely sensitive analytical methods. Fur- 
thermore, cannabinoid metabolites such as THCA are normally present in hair at even 
lower concentrations than parent cannabinoids such as THC, cannabinol, and canna- 
bidiol. This is a problem in forensic cases because passive exposure to marijuana smoke 
can result in external adsorption of cannabinoids to hair follicles. Consequently, a hair 
analysis that detects THCA provides more convincing evidence of intentional smok- 
ing or ingestion of marijuana than a hair analysis that detects THC, cannabinol, or 
cannabidiol. However, a strong case can be made for intentional marijuana use based 
on detection of THC, cannabinol, or cannabidiol if it is shown that the method of 
decontamination removes all externally adsorbed cannabinoids from the hair prior to 
hair analysis. 

Most published reviews on testing for drugs in hair primarily discuss methods 
for analysis of basic drugs such as cocaine, opiates, and amphetamines. Authors who 
have reviewed analysis of cannabinoids in hair include Staub (6), Sachs and Kintz 
(59), and Baptista et al. (60). 

Methods for the determination of cannabinoids in hair generally include the fol- 
lowing basic steps: (1) decontamination of hair by washing with a solvent to remove 
any cannabinoids adsorbed to external surfaces of the hair; (2) enzymatic or alkaline 
hydrolysis of the hair to facilitate extraction of the cannabinoids; (3) extraction of the 
digested hair; (4) derivatization of the extracted cannabinoids; and (5) analysis using 
GC and MS. The cannabinoids that appear to have the highest concentration in hair 
are THC, cannabinol, and cannabidiol. However, some of the published methods are 
designed to detect only THCA, for reasons stated above. 

Methylene chloride has been most often used for decontaminating hair prior to 
digestion (61-64); however, Strano-Rossi and Chiarotti reported that washing with 
petroleum ether was more efficient than methylene chloride for then removal of can- 
nabinoids adsorbed to hair (65). Wilkins et al. compared four different wash solvents 
(methylene chloride, methanol, isopropanol, and phosphate buffer) for analysis of THC 
in human hair from known cannabis users. The concentrations of THC were signifi- 
cantly lower when methylene chloride was used (66). 

To extract cannabinoids efficiently, the hair is first dissolved by alkaline hydrolysis 
or by enzymatic hydrolysis. Alkaline hydrolysis is generally favored because it can be 
performed very rapidly. After addition of internal standard(s) the hair is subjected to 



188 



Foltz 



NaOH (1-2 AO at 80-95°C for 10-30 minutes (61-65,67) or maintained at 37°C over- 
night (66). If the assay includes determination of drugs that are degraded in the pres- 
ence of strong alkali, (3-glucuronidase/arylsulfatase can be used to digest the hair prior 
to extraction (60). 

Early methods for the determination of cannabinoids in hair used liquid/liquid 
extraction to remove cannabinoids from the hydrolyzed hair ( 61-63, 66, 68 ) ; for example, 
after acidification, homogenized hair can be extracted with hexane:ethyl acetate (9:1 
v/v; ref. 61). A more recently published method employing enzymatic hydrolysis used 
a two-step liquid/liquid extraction procedure (60). After adjustment of the pH to 8.5, 
the hydrolyzed hair sample was extracted with chloroform :isopropanol (97:3 v/v). 
The aqueous layer was separated, acidified with acetic acid, and re-extracted with 
hexane:ethyl acetate (9:1 v/v). The two organic extracts were then combined and pre- 
pared for GC/MS analysis. 

Sachs and Dressier developed a very sensitive but lengthy assay for the detection 
of THCA in hair. The procedure involved initially extracting the hydrolyzed hair in 
hexane:ethyl acetate, washing the organic extract with 0.5 M NaOH and then with 0.1 M 
HC1, and injecting the concentrated organic extract into a high-performance liquid chro- 
matography column. The fraction containing THCA was collected, acidified with 0.05 
M phosphoric acid, and extracted with hexane:ethyl acetate. This extensive clean-up 
permitted detection of derivatized THCA at concentrations as low as 0.3 pg/mL (67). 

Other recently published methods have generally used SPE procedures, including 
solid-phase microextraction (SPME). Moore et al. used mixed-mode hydrophobic/an- 
ion exchange SPE cartridges to extract THCA from digested hair (64). After condition- 
ing the SPE cartridge, the hydrolyzed hair sample was added to the cartridge; the column 
was washed with deionized water (2 mL) and 0.1 M HChacetonitrile (70:30 v/v; 2 mL) 
and dried, after which THCA was eluted with 3 mL of hexane:ethyl acetate (75:25 v/v). 

Several variations of solid-phase microextractions have recently been used to 
extract cannabinoids from hydrolyzed hair samples. Strano-Rossi and Chiarotti devel- 
oped a relatively simple and rapid method for detection of THC, cannabinol, and can- 
nabidiol in hair based on solid-phase microextraction and GC/MS analysis (65). A 
commercially available 30-|J,m polydimethylsiloxane fiber was dipped into the neu- 
tralized hair digest for 15 minutes and then inserted directly into the injection port of 
the GC/MS, where the adsorbed nonderivatized cannabinoids were vaporized. The 
injection port temperature was 260°C; the 5% phenylmethylsilicone capillary column 
was maintained at 100°C for 2 minutes and then temperature-programmed to 270°C. 
The LODs for analysis of 50 mg of hair were 0. 1 ng/mg for THC and cannabinol and 
0.2 ng/mg for cannabidiol. 

Musshoff et al. used two variations of a headspace solid-phase microextraction 
(HS-SPME) method for determination of cannabinoids in hair. With one method a 
100-txm polydimethylsiloxane fiber was inserted for 25 minutes into the headspace of 
a heated (90°C) vial containing the digested hair (69). The fiber was then exposed to 
the headspace in a second vial containing 25 [ih of MSTFA for 8 minutes at 90°C, 
resulting in trimethylsilylation of the adsorbed cannabinoids. Finally, the fiber was 
inserted into the heated (250°C) injection port of a GC/MS, permitting the derivatized 
cannabinoids to be vaporized and analyzed. The reported LODs ranged from 0.05 to 
0.14 ng/mg for THC, cannabidiol, and cannabinol. THCA was not detected. 



Table 1 

Published Methods for Mass Spectometric Analysis of Cannabinoids in Urine 



LOQ LOD 

Ref. Analyte Extraction Derivatization Instrumentation Ionization (ng/mL) (ng/mL) Notes 



29 


THCA 


Liq/Liq 


PFPA and PFPOH 


GC/MS 


EI 


— 


— 


Discusses surface 
adsorption problems 


73 


THCA 


Liq/Liq 


BSTFA 


GC/MS 


EI 


— 


— 


Compares extraction and 
derivatization 
procedures 


1 1 




Liq/Liq 






i i 




o.y 


Derivative is more stable 
than TMS derivative 


74 


THCA 


Liq/Liq 


Trimethylsilyliodide 


GC/MS 


El 


10 


1.0 


Analyzed urine collected 
for doping analysis 


17 


THCA 


SPE 


BSTFA 


GC/MS 


EI 


2.0 


— 


Reduced solvent volume 
for SPE 


1 


1 ri v A 


or n 


ivietnyi lofliue 




111 


c 

J 




Full-scan detection on an 
ion trap MS 


26 


THCA 


SPE 


Methyl iodide 


GC/MS 


El 




2 


Extraction uses a strong 
anion exchange resin 


18 


THCA 


SPE 


BSTFA 


GC/MS 


EI 


— 


— 


Extraction uses 3 M 
Empore disk 
cartridges 


20 


THCA 


SPE 


MSTFA 


GC/MS 


El 


2.5 




Compares 2 SPE and 
derivatization 
procedures 


22 


THCA 


SPE 


MSTFA 


GC/MS 


El 


2.0 


2.0 


High throughput with 
Cerex PolyCrom-THC 
SPE 


9 


THCA and 2 
other acidic 
metabolites 


Liq/Liq 


Five procedures 
compared 


GC/MS 


El 






Compared THCA-d 3 , -d ( „ 
-d 9 , and -d 10 as internal 
standards 



(continued) 



Table 1 (continued) 



Ref. Analyte 



Extraction Derivatization 



Instrumentation Ionization 



LOQ LOD 
(ng/mL) (ng/mL) Notes 



28 
25 
75 
27 

8 

15 
12 
14 

10 
24 
71 
19 



THCA 
THCA 
THCA 
THCA 

THC and 

major 

metabolites 

THCA 

THCA 

THC and 
THCA 

THCA 

THCA 

THCA 

THCA 



Liq/Liq PFPA and PFPOH GC/MS 

See notes Methyl iodide GC/MS 

See notes Methyl iodide GC/MS 

Liq/Liq Propyl iodide GC/MS 



See notes BSTFA 

See notes MSTFA 

SPE BSTFA 

Liq/Liq BSTFA 



GC/MS 

GC/MS 
GC/MS 
GC/MS 



SPE 
SPE 

Liq/Liq BSTFA 
SPE BSTFA 



PFPA and PFPOH GC/MS 
PFPA and PFPOH GC/MS 

GC/MS/MS 
GC/MS/MS 



NCI 
EI 
EI 
El 

EI 

El 
EI 
EI 

EI 
El 
El 
EI 



— 0.7 Compares El, PCI, and 

NCI mass spectra 

— 0.5 Antibody-mediated 

extraction 

20 0.25 Extractive-alkylation 

procedure 

0.64 0.32 Derivatization with 

proply preferred to 
methyl 

— 0.5 to 2.5 Hydrolyzed with 

[3-glucuronidase. 
Extracted with an 
immunoaffinity resin. 

— — Compares 2 SPE and 2 

Liq/Liq extractions 
5 — Automated SPE 

procedure 

— — Samples hydrolyzed with 

(3-glucuronidase 

1.8 0.9 Automated SPE 

procedure 

5.0 — Compared oral fluid 

testing to urine testing 
5 Varian Saturn 2000 ion 

trap 

— — Detailed description of 

operating parameters 



30 THCA 
23 THCA 



21 

31 
10 



THCA 



SPE No derivatization LC/MS 

SPE No derivatization LC/MS 

SPE No derivatization LC/MS/MS 



THCA and Liq/Liq No derivatization LC/MS/MS 
THCA-glucuronide 

THCA and SPE No derivatization LC/MS/MS 
THCA-glucuronide 



Pos.-ESI 2.5 
Neg.-ESI — 
Neg.-APCl 5 



Pos.-ESI 
Pos.-ESI 



6.0 



10 
1.4 



Also tried negative ion 

ES1-MS 
Zorbax Eclipse XDB- 

C18LC column 
Short prep, and analysis 

time. Ret. time, 

2.4 min 
30 min. run time 

Assay used to determine 
stability of THCA and 
THCA-glucuronide in 
plasma and in urine 



THCA, 1 1 -nor-9-carboxy-A''-tetrahydrocannabinol; THC, A 9 -tetrahydrocannabinol;l_iq/l_iq, liquid/liquid extraction; PFPA, pentafluoropropionic anhydride; 
PFPOH, pentafluoropropanol; GC/MS, gas chromatography/mass spectrometry; El, electron ionization; BSTFA, bis-(trimethylsilyl)-trifluoroacetamide; 
MTBSTFA, N-methyl-N-(f-butyldimethylsilyl)-trifluoroacetamide; SPE, solid-phase extraction; MSTFA, N-methyl-/V-(trimethylsilyl)-trifluoroacetamide; NCI, 
negative ion chemical ionization; PCI, positive ion chemical ionization; ESI, electrospray ionization; APCI, atmospheric pressure chemical ionization; 
LOQ, limit of quantitation; LOD, lower limit of detection. 



Table 2 



Published Methods for Mass Spectrometric Analysis of Cannabinoids in Plasma or Serum 















LOQ 


LOD 




Ket. 


Analyte 


Extraction 


Derivatization 


Instrumentation 


Ionization 


(ng/mL) 


(ng/mL) 


Notes 


38 


lVTn 1 ti v\ \ p *>nnl vt* 3 c 

1V1U.111U1C ullt.ll y ICS 


t ■ /t ■ 


BSTFA 


nr/ivrs 


EI 






THP rRD PIRN and 5 
metabolites of THC 


if, 


Tl-TP anH 140 TT-TP 
i ri v.. tiiiu n v./ i n v^.. 


Licj/Lic[ 


TFA A 


v. J^. / IVIO 




U.Z./U.~> 




T^l— fl^ A on q li;7Pn ncmrt 

invert d.iid.iyz,cu uaiiig 
















U.111C1 C 1 H 

Hi :i r"i^7Qt"i r 7Qt"i("»n 
LIC11 Vdllid-llUll 




THCA 




1. BF 3 /MeOH 


2. TFAA 




0.2 




Early use of negative ion 
chemical ionization 


48 


THC, HO-THC, 


SPE 


Methyl iodide 


GC/MS 


EI 


0.6/0.7 3.4 


— 


Improved version of an 






and THCA 










earlier assay 




TUP TUf A anH 
ijn\^-, invert, dim 


SPF 
Ore 

HO-THC 


PFRRr 


BSTFA 


IN \^-L 


W. J/ W. J 


1.0 


Th v tvQ/"* t"i \i q 1 L'A/l nti r\r\ 
JJiAlldCLlVC d.lft.y IdlUJll 

using XAD-2 resin 




TUP an A TUfA 


SPF 


TFA A anH HFTP 




NPT 






Fnllw \7Q 1 1 H Q tf»H decmf 


8 


THC and major 


See notes 


BSTFA 


GC/MS 


EI 




0.5-2.5 


Hydrolysis with 




metabolites 














P-glucuronidase; 
extraction with an 
immunoaffinity resin; 
also analyzed 

meconium 


77 


THC, HO-THC, 


SPE 

and TUP A 

ill III J. I 1 v. / \ 


MSTFA 


GC/MS/MS 


EI 


2/5/8 


— 


Blood diluted 6:1 

U11U1 IV CAlld^LUJll 


42 


THC, HO-THC, 


SPE 

and THCA 


BSTFA 


GC/MS 


PCI 


0.5/0.5 1.0 




Plasma hydrolyzed with 
|3-glucuronidase. 
Compares 
concentrations with 
and without 
hydrolysis 


50 


THC and HO-THC 


SPE 


Tri-Sil TBT" 


GC/MS/MS 


PCI 


0.05/0.1 


0.01/0.2 


Run time, 7 min 



LOQ, limit of quantitation; LOD, lower limit of detection; Liq/Liq, liquid/liquid extraction; BSTFA, b/s-(trimethylsilyl)-trifluoroacetamide; GC/MS, gas 
chromatography/mass spectrometry; El, electron ionization; THC, AMetrahydrocannabinol; HO-THC, 1 1 -hydroxy-A 9 -tetrahydrocannabinol; TFAA, 
trifluoroacetic anhydride; NCI, negative ion chemical ionization; THCA, 1 1 -nor-9-carboxy-A 1J -tetrahydrocannabinol; SPE, solid-phase extraction; HFIP, 
hexafluoroisopropanol; MSTFA, N-methyl-N-(trimethylsilyl)-trifluoroacetamide; PCI, positive ion chemical ionization. 

"Tri-Sil TBT from Pierce Chemical Co., Rockford, IL. 



Table 3 

Published Methods for Mass Spectrometric Analysis of Cannbinoids in Whole Blood 















LOQ 


LOD 




Ref. 


Analyte 


Extraction 


Derivatization 


Instrumentation 


Ionization 


(ng/mL) 


(ng/mL) 


Notes 


78 


THC 


SPE 


TFAA 


GC/MS 


NCI 


1.0 




Initial precipitation with 
acetonitrile 


46 


THC and THCA 


SPE 


BSTFA 


GC/MS 


El 


2.0/1.0 


1.6/0.8 


Zymark RapidTrace SPE 
workstation 


43 


THC and THCA 


Liq/Liq 


Methyl iodide 


GC/MS 


El 


1.0/0.5 


— 


Extract 2 mL of blood 
with hexane:EtOAc 
(9:1) 


47 


THC and THCA 


Liq/Liq 
and SPE 


PFPA and PFPOH 


GC/MS 


El 


1.0 




THC and THCA extracts 
analyzed in separate 
runs 


45 


THC 


Liq/Liq 


PFPA and PFPOH 


GC/MS 


El 


1.0 


— 


Method fully validated; 
compared extraction 

SVJl V L. 1 1 1 a 


79 


THC and THCA 


Liq/Liq 


BSTFA 


GC/MS/MS 


El 




1.0 


Multistep extraction 
procedure 


44 


THC, HO-THC, 
and THCA 


Liq/Liq 


BSTFA 


GC/MS 


El 




0.2/0.2 


Evaluated several 
different extraction 
and derivatization 
procedures 



LOQ, limit of quantitation; LOD, lower limit of detection; THC, A 1J -tetrahydrocannabinol; SPE, solid-phase extraction; TFAA, trifluoroacetic anhydride; 
GC/MS, gas chromatography/mass spectrometry; THCA, 1 1 -nor-9-carboxy-A' ) -tetrahydrocannabinol; PFPA, pentafluoropropionic anhydride; PFPOH, 
pentafluoropropanol; Liq/Liq, liquid/liquid extraction; BSTFA, fo/s-(trimethylsilyl)-trifluoroacetamide; HO-THC, 1 1 -hydroxy-A'-tetrahydrocannabinol; NCI, 
negative ion chemical ionization; El, electron ionization. 



Table 4 

Published Method for Mass Spectrometric Analysis of Cannabinoids in Tissues 

LOQ LOD 

Ref. Analyte Extraction Derivatization Instrumentation Ionization (ng/g) (ng/g) Notes 



53 THC Liq/Liq f-Butyldimethyl GC/MS 

and SPE silylation 



54 



THC 



Liq/Liq 



Methylation 



GC/MS 



EI 



EI 



0.4 



1.0 



Very lengthy procedure; 
uses a high-resolution 
mass spectrometer 

Tissue homogenized 
with acetonitrile 



lOQ, limit of quantitation; LOD, lower limit of detection; THC, A'-tetrahydrocannabinol; Liq/Liq, liquid/liquid extraction; SPE, solid-phase 
extraction; GC/MS, gas chromatography/mass spectrometry; El, electron ionization. 



Table 5 

Published Methods for Mass Spectometric Analysis of Cannabinoids in Meconium 



Ref. 


Analyte 


Extraction 


Derivatization 


Instrumentation 


Ionization 


1 oo 

(ng/g) 


i nn 
LUU 

(ng/g) 


Notes 


56 


THCA 


Liq/Liq 


MTBSTFA 


GC/MS 


El 





2.0 


Analyzed 100 meconium 


















samples; 16 confirmed 


















positive 


55 


THC and major 


Liq/Liq 


BSTFA 


GC/MS 


El 




2.0-15 


Includes enzymatic 




metabolites 














hydrolysis; major 


















cannabinoids in 


















meconium are HO- 


THC 


































and 8(3, 11-diHO-THC 


8 


THC and major 


See notes 


BSTFA 


GC/MS 


El 




1.0-2.5 


Hydrolyzed with 




metabolites 














^-glucuronidase; 


















extracted with an 


















immunoaffinity 



LOQ, limit of quantitation; LOD, lower limit of detection; THCA, 1 1 -nor-9-carboxy-A 9 -tetrahydrocannabinol; Liq/Liq, liquid/liquid extraction; 
THC, A'-tetrahydrocannabinol; MTBSTFA, N-methyl-N-(f-butyldimethylsilyl)-trifluoroacetamide; GC/MS, gas chromatography/mass spectrometry; 
El, electron ionization; THC, A'-tetrahydrocannabinol; BSTFA, £>/s-(trimethylsilyl)-trifluoroacetamide; HO-THC, 1 1 -hydroxy-AMetrahydrocannab- 
inol. 



Table 6 

Published Methods for Mass Spectometric Analysis of Cannabinoids in Oral Fluids 



LOQ LOD 

Ref. Analyte Extraction Derivatization Instrumentation Ionization (ng/mL) (ng/mL) Notes 



58 


THC 


SPME 


None 


GC/MS 


EI 


10 


1.0 


Also analyzed 
cannabidiol and 
cannabinol 


24 


THC 


Liq/Liq 


BSTFA 


GC/MS/MS 


EI 


0.5 


0.2 


Detailed description 
of a clinical study 


57 


THC 


Liq/Liq 


PFPA 


GC/MS 


EI 






Chewing gum used to 
stimulate saliva 



LOQ, limit of quantitation; LOD, lower limit of detection; THC, A tJ -tetrahydrocannabinol; SPME, solid-phase microextraction; GC/MS, gas 
chromatography/mass spectrometry; El, electron ionization; Liq/Liq, liquid/liquid extraction; PFPA, pentafluoropropionic anhydride. 



Table 7 



Published Methods for Mass Spectometric Analysis of Cannabinoids in Hair 














LOQ 


LOD 




Ref. 


Analyte 


Extraction 


Derivatization 


Instrumentation 


Ionization 


(ng/mg) 


(ng/mg) 


Notes 


67 


THCA 


Liq/Liq 


PFPA/HFIP 


GC/MS 


NCI 


0.001 


0.0003 


HPLC cleanup to 
improve sensitivity 


80 


THCA 


SPE 


PFPA/HFIP 


GC/MS/MS 


NCI 






MS/MS more sensitivity 
than GC/MS 


61 


THC and THCA 


Liq/Liq 


PFPA/PFPOH 


GC/MS 


EI 


— 


0.1 


Analyzed hair from 43 
fatal heroin overdose 
cases 


68 


THC and THCA 


Liq/Liq 


HFBA/HFIP 


GC/MS 


EI 


0.05 


0.01 


Hair hydrolyzed with 
11.8/VKOHatRTfor 
10 min 


72 


THC and THCA 




HFBA/HFIP 


GC/MS/MS 


NCI 


0.00005 


0.00002 


Samples analyzed by 
Psychemedics Corp.; 
extraction method not 
disclosed 


65 


THC, CBD, 
and CBN 


SPME 


No derivatization 


GC/MS 


EI 




0.1 


Petroleum ether used to 
decontaminate hair 
prior to digestion 


69 


THC CRD 
and CBN 


HS-SPMF 


MSTFA 


GC/MS 


EI 


0.3 


0.05 


Annlv7pH tiair from 

marijuana users; THC 
concentration 0.3-2.2 
ng/mg 


70 


THC, CBD, 
and CBN 


HS-SPDE 


MSTFA 


GC/MS 


EI 


0.4 


0.1 


Relatively rapid 
procedure using 
HS-SPDE 



(continued) 



Table 7 (continued) 



LOQ LOD 



Ref. Analyte Extraction Derivatization Instrumentation Ionization (pg/mg) (pg/mg) Notes 



60 


THC, CBD, 
and CBN 


Liq/Liq 


No derivatization 


GC/MS 


EI 


0.1 


0.02 


Ketamine and 
Ketoprofen used as 




THCA 




PFPA/PFPOH 




NCI 


0.01 


0.005 


internal stds; hair 
hydrolyzed with (3- 
glucuronidase/ 
arylsulfatase 


62 


THCA 


Liq/Liq 


PFPA/PFPOH 


GC/MS 


NCI 


0.01 


0.005 


Monitored ions at m/z 
622, 602, 605, and 
474 


64 


THCA 


SPE 


TFAA/HFIP 


GC/MS 


NCI 


0.0005 




High-volume injector 
gave improved 
sensitivity 


66 


THC, HO-THC, 


Liq/Liq 


TFAA 


GC/MS 


NCI 


0.050/ 


0.010/ 


THCA extracted 




and THCA 




(see notes) 






0.500/ 
0.050 


0.250/ 
0.010 


separately from THC 
and HO-THC and 
derivatized by 
methylation followed 
by TFAA 


63 


THC, CBD, 
and CBJN 


Liq/Liq 


No derivatization 


GC/MS 


El 




0.1/ 
0.U2/ 
0.0 


Alkaline digest extracted 
with hexane: ethyl 
acetate (9:1) 


71 


THCA 


Liq/Liq 


BSTFA 


GC/MS/MS 


El 


5.0 




Used an ion trap mass 
spectrometer 


81 


THC, CBD, 
and CBN 


Supercritial 
fluid 

extraction 


No derivatization 


GC/MS 


El 






Primarily 
concerned with 
analysis of cocaine 
and opiates in hair 




LOQ, limit of quantitation; LOD, lower limit of detection 


; THCA, 11 -nor 


-9-carboxy-A 9 -tetrahyd 


rocannab 


inol; Liq/Liq, 


liquid/liquid extraction; PFPA, 



pentafluoropropionic anhydride; HFIP, hexafluoroisopropanol; GC/MS, gas chromatography/mass spectrometry; NCI, negative ion chemical ionization; HPLC, 
high-performance liquid chromatography; SPE, solid-phase extraction; THC, A 9 -tetrahydrocannabinol; PFPOH, pentafluoropropanol; El, electron ionization; HFBA, 
heptafluorobutyric anhydride; CBD, cannabidiol; CBN, cannabinol; HS-SPME,headspace solid-phase microextraction; MSTFA, N-methyl-N-(trimethylsilyl)- 
trifluoroacetamide; HS-SPDE, headspace solid-phase dynamic extraction; TFAA, trifluoroacetic anhydride; BSTFA, fa/s-(trimethylsilyl)-trifluoroacetamide. 



MS for Detection of Cannabinoids 



199 



The second method (70), headspace solid-phase dynamic extraction (HS-SPDE), 
used a gas-tight syringe attached to a needle internally coated with a 50-txm film of 
polydimethylsiloxane containing 10% of activated carbon (commercially available 
from Chromtech, Idstein, Germany). Hydrolysis of the hair (10 mg) took place in a 
10-mL headspace vial containing 1 mL of 1 M NaOH, 0.5 g of sodium carbonate, and 
the THC-d 3 internal standard. The sample solution was heated at 90°C for 5 minutes 
and stirred by a magnetic mixer bar. The SPDE needle was inserted into the sample 
vial through a septum and the syringe plunger was moved up and down slowly 30 
times aspirating and dispensing a vapor volume of 1 mL to extract the analytes from 
the headspace dynamically. In the same manner as the HS-SPME method, the needle 
was removed and inserted into a second vial containing the derivatizing reagent. 
Exposure to the derivatizing reagent vapor occurred by moving the syringe plunger up 
and down six times over a 4-minute period. The syringe was then removed from the 
vial, the needle inserted into the hot injection port of the GC/MS, and the plunger 
slowly moved down, thereby flushing the analytes into the GC column. 

The HS-SPME and HS-SPDE methods gave very similar results in terms of lower 
limits of detection and quantitation, precision and accuracy, and extraction recoveries. 
However, the SPDE needle with the internal coating is far more robust than the SPME- 
coated fiber, has greater capacity, and is usable for more than 350 samplings (70). 

Some of the published assays for determination of cannabinoids in hair do not 
derivatize prior to GC/MS analysis (61,63,65). Trimethylsilylation with BSTFA or 
MSTFA has been used for analysis of cannabinoids in hair (65,70,71) but so far has 
not provided the sensitivity required to detect THCA in hair from cannabis users. The 
best sensitivities have been achieved by derivatization with a combination of a 
perfluorinated anhydride (TFAA, PFPA, or HFBA) and a perfluorinated alkyl alcohol 
(HFIP or PFPOH). Derivatization with these reagents increases the molecular weights 
of the cannabinoid analytes, often resulting in improved chromatography and selec- 
tivity. An even greater benefit is the fact that perfluorinated derivatives are much 
more efficiently ionized by NCI than by electron ionization, often resulting in dra- 
matically improved sensitivity (60,62,64,67,72). 

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MS for Detection of Cannabinoids 



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etry. Clin. Chem. 48, 301-306. 

33. Brunk, S. D. (1988) False negative GC/MS assay for carboxy THC due to ibuprofen inter- 
ference. J. Anal. Toxicol. 12, 290-291. 

34. Stout, P. R., Horn, C. K., and Lesser, D. R. (2000) Loss of THCCOOH from urine speci- 
mens stored in polypropylene and polyethylene containers at different temperatures. /. 
Anal. Toxicol. 24, 567-571. 

35. Blanc, J. A., Manneh, V. A., Ernst, R., et al. (1993) Adsorption losses from urine-based 
cannabinoid calibrators during routine use. Clin. Chem. 39, 1705-1712. 

36. Joern, W .A. (1992) Surface adsorption of the urinary marijuana carboxy metabolite: The 
problem and a partial solution. J. Anal. Toxicol. 16, 401. 

37. Tsai, J. S. C, ElSohly, M. A., Tsai, S. F., Murphy, T. P., Twarowska, B., and Salamone, S. 
J. (2000) Investigation of nitrite adulteration on the immunoassay and GC-MS analysis of 
cannabinoids in urine specimens. J. Anal. Toxicol. 24, 708-714. 

38. Kemp, P. M., Abukhalaf, I. K., Manno, J. E., Manno, B. R., Alford, D. D., and Abusada, G. 
A. (1995) Cannabinoids in humans. I. Analysis of A9-tetrahydrocannabinol and six me- 
tabolites in plasma and urine using GC/MS. J. Anal. Toxicol. 19, 285-291. 

39. Kemp, P. M., Abukhalaf, I. K, Manno, J. E., et al. (1995) Cannabinoids in humans. II. The 
influence of three methods of hydrolysis on the concentration of THC and two metabolites 
in urine. J. Anal. Toxicol. 19, 292-298. 

40. ElSohly, M. A., Feng, S., Murphy, T. P., Ross, S. A., Nimrod, A., Mehmedic, Z., and 
Fortner, N. (1999) A9-Tetrahydrocannabivarin (A9-THCV) as a marker for the ingestion 
of cannabis versus Marinol®. J. Anal. Toxicol. 23, 222-224. 

41. ElSohly, M. A., Feng, S., Murphy, T. P., et al. (2001) Identification and quantitation of 11- 
nor-A9-tetrahydrocannabivarin-9-carboxylic acid, a major metabolite of A9- 
tetrahydrocannabivarin. J. Anal. Toxicol. 25, 476-480. 



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42. Gustafson, R. A., Moolchan, E. T., Barnes, A., Levine, B., and Huestis, M. A. (2003) 
Validated method for the simultaneous determination of A9-tetrahydrocannabinol (THC), 
1 1-hydroxy-THC and 1 l-nor-9-carboxy-THC in human plasma using solid phase extrac- 
tion and gas chromatography-mass spectrometry with positive chemical ionization. /. 
Chromatogr. B 798, 145-154. 

43. Kintz, P. and Cirimele, V. (1997) Testing human blood for cannabis by GC-MS. Biomed. 
Chromatogr. 11, 371-373. 

44. Goodall, C. R. and Basteyns, B. J. (1995) A reliable method for the detection, confirma- 
tion, and quantitation of cannabinoids in blood. J. Anal. Toxicol. 19, 419-426. 

45. Chu, M. H. C. and Drummer, O. H. (2002) Determination of A9-THC in whole blood using 
gas chromatography-mass spectrometry. /. Anal. Toxicol. 26, 575-581. 

46. D'Asaro, J. A. (2000) An automated and simultaneous solid-phase extraction of A9-tet- 
rahydrocannabinol and 1 l-nor-9-carboxy- A9-tetrahydrocannabinol from whole blood us- 
ing the Zymakr RapidTrace with confirmation and quantitation by GC-EI-MS. /. Anal. 
Toxicol. 24, 289-295. 

47. Felgate, P. D. and Dinan, A. C. (2000) The determination of A9-tetrahydrocannabinol and 
1 l-nor-9-carboxy-A9-tetrahydrocannabinol in whole blood using solvent extraction com- 
bined with polar solid-phase extraction. J. Anal. Toxicol. 24, 127-132. 

48. Steinmeyer, S., Bregel, D., Warth, S., Kraemer, T., and Moeller, M. R. (2002) Improved 
and validated method for the determination of A9-tetrahydrocannabinol (THC), 1 1-hy- 
droxy-THC and 1 l-nor-9-carboxy-THC in serum, and in human liver microsomal prepara- 
tions using gas chromatography-mass spectrometry. /. Chromatogr. B 772, 239-248. 

49. Huang, W., Moody, D. E., Andrenyak, D. M., et al. (2001) Simultaneous determination of 
A9-tetrahydrocannabinol and 1 l-nor-9-carboxy- A9-tetrahydrocannabinol in human plasma 
by solid-phase extraction and gas chromatography-negative ion chemical ionization mass 
spectrometry. J. Anal. Toxicol. 25, 531-537. 

50. Nelson, C. C, Fraser, M. D., Wilfahrt, J. K., and Foltz, R. L. (1993) Gas chromatography 
tandem mass spectrometry measurement of A(9)-tetrahydrocannabinol, naltrexone, and 
their active metabolites in plasma. Ther. Drug Monit. 15, 557-562. 

51. Hughes, J. M., Andrenyak, D. M., Crouch, D. J., and Slawson, M. (2003) Comparison of LC/ 
MS ionization techniques for cannabinoids in blood (Abstract). J. Anal. Toxicol. 27, 191. 

52. Mireault, P. (1998) Analysis of A9-THC and its two metabolites by APCI-LC/MS. ASMS 
Conference, Orlando, CA, (Abstract). 

53. Johansson, E., Noren, K., Sjoevall, J., and Halldin, M.M. (1989) Determination of Al- 
tetrahydrocannabinol in human fat biopsies from marijuana users by GC/MS. Biomed. 
Chromatogr. 3, 35-38. 

54. Kudo, K., Nagata, T., Kimura, K., Imamura, T., and Jitsufuchi, N. (1995) Sensitive determi- 
nation of A9-tetrahydrocannabinol in human tissue by GC/MS. /. Anal. Toxicol. 19, 87-90. 

55. ElSohly, M. A. and Feng, S. (1998) A9-THC metabolites in meconium: Identification of 
11-OH-A9-THC, 8(3,1 1-diOH- A9-THC, and 1 l-nor-A9-THC-9-COOH as major metabo- 
lites of A9-THC. J. Anal. Toxicol. 22, 329-335. 

56. Moore, C, Lewis, D., Becker, J., and Leikin, J. (1996) The determination of 11 nor-A9- 
tetrahydrocannabinol-9-carboxylic acid in meconium. J. Anal. Toxicol. 20, 50-54. 

57. Menkes, D. B., Howard, R. C, Spears, G. F. S., and Cairns, E. R. (1991) Salivary THC 
following cannabis smoking correlates with subjective intoxication and heart rate. Psy- 
chopharmacology 103, 277-279. 

58. Hall, B. J., Satterfield-Dover, M., Parikh, A. R., and Brodbelt, J. S. (1998) Determination 
of cannabinoids in water and human saliva by solid-phase microextraction and quadrupole 
ion trap GC/MS. Anal. Chem. 70, 1788-1796. 

59. Sachs, H. and Kintz, P. (1998) Testing for drugs in hair — critical review of chromato- 
graphic procedures since 1992 — review. J. Chromatogr. B 713, 147-161. 



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60. Baptista, M. J., Monsanto, P. V., Pinho Marques, E. G., et al. (2002) Hair analysis for A9- 
THC, A9-THC-COOH, CBN and CBD, by GC/EI-MS Comparison with GC/MS-NCI for 
A9-THC-COOH. Forensic Sci. Int. 128, 66-78. 

61. Cirimele, V., Kintz, P., and Mangin, P. (1995) Testing of human hair for cannabis. Foren- 
sic Sci. Int. 70, 175-182. 

62. Kintz, P., Cirimele, V., and Mangin, P. (1995) Testing human hair for cannabis. II. Identi- 
fication of THC-COOH by GC/NCI-MS as a unique proof. J. Forensic Sci. 40, 619-622. 

63. Cirimele, V., Sachs, H., Kintz, P., and Mangin, P. (1996) Testing human hair for cannabis. 
III. Rapid screening procedure for the simultaneous identification of A9-tetrahydrocannab- 
inol, cannabinol, and cannabidiol. J. Anal. Toxicol. 20, 13-16. 

64. Moore, C, Guzaldo, F., and Donahue, T. (2001) The determination of 1 1-nor- A9-tetrahy- 
drocannabinol-9-carboxylic acid (THC-COOH) in hair using negative ion GC/MS and 
high-volume injection. /. Anal. Toxicol. 25, 555-558. 

65. Strano-Rossi, S. and Chiarotti, M. (1999) Solid-phase microextraction for cannabinoids 
analysis in hair and its possible application to other drugs. /. Anal. Toxicol. 23, 7-10. 

66. Wilkins, D. G., Haughey, H., Cone, E. J., Huestis, M. A., Foltz, R. L., and Rollins, D. E. 
(1995) Quantitative analysis of THC, 1 1-OH-THC, and THCCOOH in human hair by nega- 
tive ion chemical ionization mass spectrometry. /. Anal. Toxicol. 19, 483-491. 

67. Sachs, H. and Dressier, U. (2000) Detection of THC-COOH in hair by MSD-NCI after 
HPLC clean-up. Forensic Sci. Int. 107, 239-247. 

68. Jurado, C, Gimenez, M. P., Menendez, M., and Repetto, M. (1995) Simultaneous quanti- 
fication of opiates, cocaine and cannabinoids in hair. Forensic Sci. Int. 70, 165-174. 

69. Musshoff, F., Junker, H. P., Lachenmeier, D. W., Kroener, L., and Madea, B. (2002) Fully 
automated determination of cannabinoids in hair samples using headspace solid-phase 
microextraction and gas chromatography-mass spectrometry. J. Anal. Toxicol. 26, 554-560. 

70. Musshoff, F., Lachenmeier, D. W., Kroener, L., and Madea, B. (2003) Automated 
headspace solid-phase dynamic extraction for the determination of cannabinoids in hair 
samples. Forensic Sci. Int. 133, 32-38. 

71. Chiarotti, M. and Costamagna, L. (2000) Analysis of 1 l-nor-9-carboxy-A9-tetrahydrocan- 
nabinol in biological samples by GC/MS/MS. Forensic Sci. Int. 114, 1-6. 

72. Mieczkowski, T. (1995) A research note: The outcome of GC/MS/MS confirmation of hair 
assays on 93 cannabinoid-positive cases. Forensic Sci. Int. 70, 83-91. 

73. Baker, T. S., Harry, J. V., RusseU, J. W., and Myers, R .L. (1984) Rapid method for the GC/MS 
confirmation of ll-nor-9-carboxy-A9-tetrahydrocannabinol in urine. /. Anal. Toxicol. 8, 255-259. 

74. De Cock, K. J. S., Delbeke, F. T., De Boer, D., Van Eenoo, P., and Roels, K. (2003) 
Quantitation of 1 l-nor-A9-tetrahydrocannabinol-9-carboxylic acid with GC/MS in urine 
collected for doping analysis. /. Anal. Toxicol. 27, 106-109. 

75. Lisi, A. M., Kazlauskas, R., and Trout, G. J. (1993) Gas chromatographic-mass spectro- 
metric quantitation of urinary 1 l-nor-A9-tetrahydrocannabinol-9-carboxylic acid after 
derivatization by extractive alkylation. /. Chromatogr. 617, 265-270. 

76. Foltz, R. L., McGinnis, K. M., and Chinn, D. M. (1983) Quantitative measurement of A9- 
tetrahydrocannabinol and two major metabolites in physiological specimens using capil- 
lary column gas chromatography/negative ion chemical ionization mass spectrometry. 
Biomed. Mass Spectrom. 10, 316-323. 

77. Weller, J. -P., Wolf, M., and Szidat, S. (2000) Enhanced sensitivity in the determination of 
A9-tetrahydrocannabinol and two major metabolites in serum using ion-trap GC/MS/MS. 
J. Anal. Toxicol. 24, 359-364. 

78. Stonebraker, W. E., Lamoreaux, T. C, Bebault, M., Rasmussen, S. A., Jepson, B. R., and 
Beck, B. K. (1998) Robotic solid-phase extraction and GC/MS analysis of THC in blood. 
Am. Clin. Lab. 17, 18-19. 



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79. Collins, M., Easson, J., Hansen, G., Hodda, A., and Lewis, K. (1997) GC/MS/MS confir- 
mation of unusually high A9-tetrahydrocannabinol levels in two postmortem blood 
samples. /. Anal. Toxicol. 21, 538-542. 

80. Uhl, M. (1997) Determination of drugs in hair using GC/MS/MS. Forensic Sci. Int. 84, 
281-294. 

81. Cirimele, V., Kintz, P., Majdalani, R., and Mangin, P. (1995) Supercritical fluid extraction 
of drugs in drug addict hair. J. Chromatogr. B Biomed. Appl. 673, 173-181. 

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determination of cannabinoids in plasma. Anal. Chem. 58, 716-721. 



Chapter 9 



Human Cannabinoid 
Pharmacokinetics and Interpretation 
of Cannabinoid Concentrations 
in Biological Fluids and Tissues 

Marilyn A. Huestis and Michael L. Smith 

1. Introduction 

Pharmacokinetics is the study of the absorption, distribution, metabolism, and 
elimination of a drug in the body and how these processes change with time. Follow- 
ing controlled drug administration, scientists monitor the drug and its metabolites in 
bodily fluids and tissues to develop a pharmacokinetic profile for the animal or human 
being studied. After years of research, scientists have learned some important general 
principles about pharmacokinetic profiles. One is that, in general, pharmacokinetic 
profiles are similar for most animals and humans, but specific elements of the disposi- 
tion of a drug in the body can differ greatly between species and between subjects 
within a species. Another principle is that helpful models can be developed that char- 
acterize a drug's pharmacokinetics and define parameters to describe processes such 
as time to peak and maximum concentrations, half-lives, volumes of distribution, and 
so on. Measuring these pharmacokinetic parameters facilitates comparison between 
and within human subjects who are examined at different times following administra- 
tion of a drug. As specific examples in this chapter will convey, it is important to 
conduct carefully controlled studies and astutely note inter- and intrasubject similari- 
ties and differences in pharmacokinetic parameters to build databases that can be used 
to answer real life questions. The third principle that we will consider is that pharma- 
cokinetic profiles change with the route of drug administration. 

From: Forensic Science and Medicine: Marijuana and the Cannabinoids 
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey 



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In this chapter, we describe what is currently known about the pharmacokinetics 
of A 9 -tetrahydrocannabinol (THC), the principal psychoactive component of cannabis 
(1,2). Our focus is THC because the majority of scientific studies have targeted this 
drug and its metabolites, although 64 different cannabinoids have been identified in 
the Cannabis plant (3-9). Routes of administration and comparisons of pharmacoki- 
netic parameters between human subjects have been published and are examined to 
develop a relationship to a drug's pharmacodynamic effects. In the Interpretation of 
Body Fluid and Hair Concentrations section of this chapter, we discuss how one uses 
the relationship between the pharmacokinetics of THC and its pharmacodynamic effects 
to interpret concentrations of cannabinoids in biological fluids and tissues with the 
ultimate goal of answering important social and scientific questions. Some typical 
questions might involve the following areas: 

1 . Social scenarios: If a man is arrested for driving erratically and triers of fact in a court 
of law subsequently hear testimony that his plasma concentration of THC is 2 ng/mL, 
can they infer that the marijuana he previously smoked contributed to his impaired 
driving? Should the laboratory that analyzed the plasma specimen have measured 
metabolites of THC to better answer this question? Could the same information be 
obtained by analyzing oral fluid, a specimen that can be obtained less invasively? 
Would analysis of the man's hair for THC help the jurors determine if he was a chronic 
cannabis user? These questions indicate some typical problems encountered by indi- 
viduals who must evaluate human performance. Similar questions arise in workplace 
drug testing and death investigations. 

2. Scientific scenarios: Scientists investigating cannabinoid mechanisms of action are 
also interested in their pharmacokinetics (2). Sites of action are often within the brain 
or peripheral nerve tissues, and it is important to understand the processes and time 
frames for the drugs to reach and leave these sites (10,11). Imaging technology mea- 
suring physiological functions such as cerebral blood flow (CBF) or other blood oxy- 
gen level-dependent function has allowed more sophisticated studies of drug uptake 
and distribution to cannabinoid receptor sites. It is important to relate these physi- 
ological functions to a drag's pharmacokinetic profile in plasma and other fluids 
(12,13). Questions from these scientists might be: Do the concentrations of THC in 
plasma correlate with changes in CBF following cannabis use? Can measurement of 
THC concentrations help us to understand individual variations in CBF and effects of 
cannabis? 

A representative clinical investigator might ask, can we use plasma cannabinoid 
concentrations to manage patients prescribed a cannabis preparation to treat neuro- 
pathic pain, appetite loss with AIDS wasting disease, nausea and vomiting following 
chemotherapy, or symptoms of multiple sclerosis? Research scientists and medical 
practitioners have begun to use cannabinoids to treat these and similar illnesses ( 14- 
17). As with any therapeutic drug, understanding its pharmacokinetics is important in 
managing patients to maximize clinical effectiveness and reduce toxicity. It is also 
important in determining the abuse liability of a drug preparation. These and addi- 
tional questions will be addressed in this chapter. 



Human Cannabinoid Pharmacokinetics 



207 



2. Cannabis Potency 

Dose, chemical structure of precursors, binding of THC to macromolecules in 
cannabis plant material, and route of administration affect the amount of THC absorbed. 
The concentrations of THC in different cannabis products have been determined ( 18,19). 
The most comprehensive report, by ElSohly et al., examined marijuana, hashish, and 
hashish oil samples seized across the United States by the Drug Enforcement Admin- 
istration over an 18 -year period (20). THC content increased from an average of 1.5% 
in 1980 to 4.2% in 1997. Interestingly, THC content in hashish and hashish oil averag- 
ing 12.9% and 17.4%, respectively, did not show an increase over time. Government 
laboratories in the United States have confirmed this trend toward higher-potency mari- 
juana (21 ). 

The chemical structure of cannabinoids in marijuana is also important. About 
95% of THC present in marijuana plant material is in the form of two carboxylic acids 
that are converted to THC during smoking (3,22). Scientists originally believed that if 
a person orally ingested marijuana without heating, very little THC would be absorbed. 
They had evidence that if one heated marijuana before ingestion, as occurs with mari- 
juana brownies, significant quantities of THC were absorbed. Later studies demon- 
strated that an individual can also absorb THC from marijuana plants that were dried 
in the sun, because variable amounts of THC released by decarboxylation. Hashish 
and hashish oil retain much of the parent THC in a form that can be more easily 
absorbed, whether smoked or ingested orally. 

3. Absorption 

Smoking, the principal route of cannabis administration in the United States, 
provides a rapid and highly efficient method of drug delivery. Approximately 30% of 
THC in marijuana or hashish cigarettes is destroyed by pyrolysis during smoking 
(23,24). Smoked drugs are highly abused in part because of the efficiency and speed 
of delivery of the drug from the lungs to the brain. Intensely pleasurable and strongly 
reinforcing effects may be produced because of the almost immediate drug exposure 
to the central nervous system. Drug delivery during cannabis smoking is characterized 
by rapid absorption of THC, with slightly lower peak concentrations than those found 
after intravenous administration (25). Bioavailability of smoked THC is reported to 
be 18-50% partly as a result of the intra- and intersubject variability in smoking 
dynamics that contribute to uncertainty in dose delivery (26). The number, duration, 
and spacing of puffs, hold time, and inhalation volume greatly influence the degree of 
drug exposure (27-29). THC can be measured in the plasma within seconds after 
inhalation of the first puff of marijuana smoke (see Fig. 1; ref. 30). Mean ± SD THC 
concentrations of 7.0 ±8.1 and 18.1 ± 12.0 ng/mL were observed following the first 
inhalation of a low- (1.75% THC, approx 16 mg) or high-dose (3.55% THC, approx 
30 mg) cigarette, respectively (30). Concentrations increased rapidly and peaked at 
9.0 minutes, berfore initiation of the last puff sequence at 9.8 minutes. Figure 2 dis- 



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Huestis and Smith 




Minutes 

Fig. 1 . Mean (N = 6) plasma concentrations of A 9 -tetrahydrocannabinol (THC), 1 1 - 
hydroxy-A 9 -THC (1 1-OH-THC), and 1 1 -nor-9-carboxy-A 9 -THC (THCCOOH) by gas 
chromatography/mass spectrometry during smoking of a single 3.55% THC cigarette 
Each arrow represents one inhalation or puff on the cannabis cigarette. (From ref. 1 
with permission.) 



160 n 




Smoking 

Fig. 2. Mean (N = 6) plasma concentrations of A 9 -tetrahydrocannabinol (THC), 1 1 - 
hydroxy-A 9 -THC (1 1-OH-THC), and 1 1 -nor-9-carboxy-A 9 -THC (THCCOOH) by gas 
chromatography/mass spectrometry following smoking of a single 3.55% THC 
cigarette. (From ref. 30 with permission.) 



Human Cannabinoid Pharmacokinetics 



209 



300 - 




Smoking 

Fig. 3. Individual plasma A 9 -tetrahydrocannabinol (THC) time course by gas chroma- 
tography/mass spectrometry for six subjects following smoking of a single 3.55% 
THC cigarette. (From ref. 30 with permission) 



plays mean data for a group of six subjects after paced smoking of a single 3.55% 
THC cigarette. The number of puffs, length of inhalation and hold time, time between 
puffs, and potency of the cigarette were controlled. Figure 3 shows individual THC 
concentration time profiles for six subjects and demonstrates the large intersubject 
variability of the smoked route of drug administration. Many individuals prefer the 
smoked route, not only for its rapid drug delivery, but also for the ability to titrate 
their dose. 

In some studies THC was measured in blood, and expected values were found to 
be about half those of plasma (31). Albumin and other proteins that bind THC and the 
poor penetration of THC into red blood cells contribute to these higher plasma con- 
centrations. Postmortem blood is a common example where blood concentrations are 
routinely reported because of difficulty obtaining acceptable plasma samples. Signifi- 
cant differences in THC concentrations between the two fluids make it important to 
always be informed about which is being reported. 

If cannabis is ingested orally, absorption is slower and peak plasma THC con- 
centrations are lower (25,32-34). Wall et al. found peak THC concentrations approx 
4-6 hours after ingestion of 15-20 mg of THC in sesame oil (34). Peak THC concen- 
trations ranging from 4.4 to 1 1 ng/mL were observed 1-5 hours following ingestion of 
20 mg of THC in a chocolate cookie (25). Oral bioavailability has been reported to be 
4-20% (25,34), in part as a result of degradation of drug in the stomach (35). Also, 
there is significant first-pass metabolism to active 1 1 -hydroxy- A 9 -tetrahydrocannab- 
inol (1 1-OH-THC) and inactive metabolites. Plasma 1 1-OH-THC concentrations range 
from 50 to 100% of THC concentrations following the oral route of cannabis adminis- 



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Huestis and Smith 



tration compared to only about 10% after smoking (34). 1 1-OH-THC is equipotent to 
THC, explaining the fact that pharmacodynamic effects after oral cannabis adminis- 
tration appear to be greater than those after smoking THC at the same concentrations 
(25). 

4. Distribution 

THC has a large volume of distribution, 10 L/kg, and is 97-99% protein bound 
in plasma, primarily to lipoproteins (36,37). Highly perfused organs, including the 
brain, are rapidly exposed to drug. Less highly perfused tissues accumulate drug more 
slowly because THC redistributes from the vascular compartment to tissue (38). THC s 
high lipid solubility concentrates and prolongs retention of the drug in fat (39,40). 
Slow release of the drug from fat and significant enterohepatic circulation contribute 
to THC's long terminal elimination half-life in plasma, reported as greater than 4.1 
days in chronic marijuana users (41). Isotopically labeled THC and sensitive analyti- 
cal procedures were used to obtain this estimate of drug half-life. Use of less sensitive 
assays and a shorter monitoring time yield much lower estimates of terminal elimina- 
tion half-life. 

5. Metabolism 

Hydroxylation of THC by the hepatic cytochrome P450 enzyme system leads to 
production of the active metabolite 1 1-OH-THC (42,43), believed by early investiga- 
tors to be the true active analyte (44). When marijuana is smoked as opposed to taken 
orally, concentrations of 1 1-OH-THC are much lower (approx 10% of the THC con- 
centration; ref. 30). Other tissues, including brain, intestine, and lung, may contribute 
to the metabolism of THC, and, in these tissues, alternate hydroxylation pathways 
may be more prominent (45^49). Further metabolism to di- and tri-hydroxy compounds, 
ketones, aldehydes, and carboxylic acids has been documented (38,50). Oxidation of 
active 1 1-OH-THC produces the inactive metabolite, 1 l-nor-9-carboxy-A 9 -tetrahydro- 
cannabinol (THCCOOH) (44,51). In a study of the pharmacokinetics of a single oral 
10-mg dose of Marinol®, the concentration of inactive THCCOOH metabolite pre- 
dominated from as early as 1 hour after dosing, with much lower THC and 1 1-OH- 
THC concentrations (52). The inactive THCCOOH metabolite and its glucuronide 
conjugate have been identified as the major end products of biotransformation in most 
species, including humans (50,53). Renal clearance of these polar metabolites is low 
as a result of extensive protein binding (36). Plasma THCCOOH concentrations gradu- 
ally increase and are greater than THC concentrations shortly after smoking (Fig. 2), 
whereas THC concentrations decrease rapidly after smoking cessation (30). The time 
course of detection of THCCOOH in plasma is much longer than that of THC or 1 1- 
OH-THC. 

6. Elimination 

After the initial distribution phase, the rate-limiting step in the elimination of 
THC is its redistribution from lipid depots to blood (54). Early studies showed that 



Human Cannabinoid Pharmacokinetics 



211 




Hours 

Fig. 4. Urinary excretion profile of 1 1 -nor-9-carboxy-A 9 -THC (THCCOOH) as mea- 
sured by gas chromatography/mass spectrometry (GC/MS) in one subject following 
smoking of a single 3.55% THC cigarette. The horizontal line at 1 5 ng/mL represents 
the current GC/MS cutoff used in most testing programs. The urinary THC-COOH 
concentrations (ng/mL) normalized to urine creatinine concentrations (mg/mL) are 
illustrated with closed triangles. (From ref. 89 with permission.) 



15-20% of a smoked THC dose was eliminated as acidic urinary metabolites, whereas 
25-30% were excreted in the feces as 1 1-OH-THC and THC-COOH following intra- 
venous administration and 48-53% following oral administration (34,38). Approxi- 
mately 80% of the acidic urinary metabolites are estimated to be conjugated and 
nonconjugated THC-COOH. There appears to be no significant difference in metabo- 
lism between men and women (34). A total of 80-90% of the drug is excreted within 
5 days, mostly as hydroxylated and carboxylated metabolites (38). Halldin et al. iden- 
tified 18 acidic metabolites of THC in urine, most of which are hydroxylated or (3- 
oxidized analogs of THC (53). Many of these metabolites are conjugated with 
glucuronic acid, increasing the compounds' water solubility. The primary urinary 
metabolite is the acid-linked THCCOOH glucuronide conjugate (55), whereas 11- 
OH-THC predominates in the feces (38). Mean peak urinary concentrations of THC- 
COOH were 89.8 ± 31.9 ng/mL and 153.4 ± 49.2 ng/mL approx 8 and 14 hours after 
smoking a single 1.75 or 3.55% THC cigarette (see Fig. 4; refs. 56 and 57). THC- 
COOH was detected in urine at a concentration greater than or equal to 15 ng/mL for 
33.7 ± 9.2 hours and 88.6 ± 9.5 hours after these doses (15 ng/mL was selected for 
evaluation because federal drug testing programs administratively designate speci- 
mens with THCCOOH concentrations below this level as negative). When sensitive 
analytical procedures and sufficient sampling periods are employed, the terminal uri- 
nary excretion half-life of THCCOOH in humans has been estimated to be 3—4 days 
(58). When THC is ingested orally, the excretion profile is similar to that following 
smoking (32,59). Gustafson et al. studied seven subjects who received oral doses of 0, 
0.39, 0.47, 7.5 (Marinol), and 14.8 mg THC per day in a double-blind, placebo-con- 



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Huestis and Smith 



trolled, randomized study (60). THC in hemp oil or Marinol was administered in three 
divided daily doses at meals for 5 days. All urine specimens were collected over the 
10-week study period and analyzed by several immunoassays and gas chromatogra- 
phy/mass spectrometry (GC/MS). Maximum THC-COOH concentrations were 5.4- 
38.2 ng/mL and 19.0-436 ng/mL for the two lower and two higher doses, respectively. 

An important analytical study was published by Kemp et al. showing that sig- 
nificantly higher concentrations of THC and 1 1-OH-THC in urine were found when 
Escherichia coli (3-glucuronidase was employed in the hydrolysis method compared 
with either of the common hydrolysis methods using Helix pomatia glucuronidase or 
base (61 ). Mean THC concentration in urine specimens from seven subjects collected 
after each had smoked a single 3.58% marijuana cigarette was 22 ng/mL using the E. 
coli glucuronidase hydrolysis method, whereas THC concentrations using either H. 
pomatia glucuronidase or base hydrolysis methods were near zero. Similar differ- 
ences were found for 1 1-OH-THC with a mean concentration of 72 ng/mL from the E. 
coli method and concentrations less than 10 ng/mL from the other methods. It is hoped 
that the finding of THC in urine may provide a reliable marker of recent cannabis use; 
however, adequate data from controlled drug administration studies are not yet avail- 
able. 

7. Interpretation of Body Fluid and Hair Concentrations 

Interpreting body fluid concentrations by necessity depends on the nature of the 
questions that require a science-based answer; however, the most common social ques- 
tions generally can be summarized as: Is the concentration of the drug in an individual's 
body fluid sufficiently high to indicate impairment or place them in violation of a 
governing policy? 

Research scientists who are conducting studies to determine cannabinoid mecha- 
nisms of action or examine how cannabinoids may be used in clinical treatment also 
have an interest in interpreting cannabinoid concentrations in body fluids and tissues. 
The generic question they might ask would be: How do fluid or tissue concentrations 
in humans correlate with brain concentrations or with treatment outcome? To provide 
answers to these important social and scientific questions, we must examine more 
closely the kinetics of the drug in bodily fluids and tissues and how these relate to 
effects on the individual. 

7.1. Plasma 

Let us consider the specific example of a man who is stopped by a police officer 
for erratic driving. The driver fails a field sobriety test indicating that he is impaired, 
and subsequent laboratory testing determines that his plasma THC concentration is 
2 ng/mL. Did the THC contribute to his impaired driving? 

Plasma concentrations of drug are frequently measured in an attempt to answer 
this question because, in general, plasma concentrations of most drugs correlate with 
drug effects better than concentrations in other bodily fluids. Mason and McBay 
reported in 1985 that one could not predict the effects of cannabis from plasma THC 
concentrations (62). They quoted their own study of 600 drivers killed in single- vehicle 



Human Cannabinoid Pharmacokinetics 



213 



i 




Model I 



Model II 



01 




.01 



-tiht|- -i-TT-iry--n-.il. i ™ 

.01 .1 1 10 100 1000 
THCCOOH/THC 



1 



Fig. 5. Predictive mathematical models for estimating the elapsed time in hours of last 
cannabis use based on plasma A 9 -tetrahydrocannabinol (THC) and 1 1 -nor-9-carboxy- 
A 9 -THC (THCCOOH) concentrations by GC/MS. (From ref. 70 with permission.) 

crashes that found alcohol to be the only drug with significant adverse effects on driv- 
ing (31). Moskowitz, reporting during the same time frame, did not specifically address 
plasma concentrations of THC, but cited many studies that found a relationship between 
cannabis dose and performance impairment including impaired coordination, track- 
ing, perception, and vigilance in driving simulators and on-the-road tests (63). More 
recent studies with carefully controlled variables and newer performance measures 
documented that smoking cannabis at doses of 300 [ig THC/kg, or about 20 mg for the 
70-kg man in our example, impaired perceptual motor speed, accuracy, and multi- 
tasking, all important requirements for safe driving (64-66). The impairing effects of 
the 300 M-g/kg dose of THC were similar to those of individuals with blood alcohol 
concentrations of 0.05 g/dL or greater, the legal driving limit in most European coun- 
tries. When combined with alcohol, the impairing effects of THC were even greater 
(66-68). However, most of these studies did not attempt to correlate plasma or blood 
THC concentrations with observed effects but demonstrated that impairment depended 
on the time after use, with most subjects showing no impairment 24 hours postdose. 
Huestis et al. performed controlled administration studies that measured plasma THC 
concentrations in six individuals who had smoked 15.8- and 33-mg doses of THC in 
marijuana (69). Concentrations for plasma collected after marijuana smoking were 
used to construct models for predicting the time of last THC use within 95% confi- 
dence intervals (see Fig. 5; refs. 30, 70, and 71). Both Model I, which used plasma 
THC concentrations, and Model H, which used the ratio of THCCOOH/THC con- 
centrations, were found to predict the time of last use in about 90% of cases from all 
previously published plasma concentration data, whether analysis was by radioimmuno- 



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assay (RIA), GC, or GC/MS. These mathematical models were further evaluated in 
another controlled drug administration study of 38 subjects, each smoking a 2.64% 
THC cigarette. Of these subjects, 29 smoked a second cigarette 4 hours later (72). Plasma 
was collected immediately after the first cigarette and up to 6 hours after smoking for 
analysis of THC and THC-COOH concentrations (N = 111). Accuracy, when applying 
the combination of Model I and Model II's 95% confidence intervals, following the first 
cigarette was 99.5% (413 of 415 specimens had a THC concentration or THC-COOH/ 
THC ratio that predicted the correct time of use within this interval) with no underesti- 
mations of time of use and maximum overestimation of 4 minutes. Accuracy when 
applying the combined models' 95% confidence intervals following the second ciga- 
rette was 98.6% (285 of 289 specimens) with no underestimations and the same maxi- 
mum overestimation. When plasma concentrations of THC were between 0.5 and 2 ng/ 
mL, Model I alone was 80.5% accurate, and Model II alone was 77.6% accurate. How- 
ever, Model I had no underestimations, and Model II had time of use for 17 of 76 speci- 
mens underestimated with maximum errors up to 1.5 hours, indicating that Model II 
alone is less reliable when THC concentrations are between 0.5 and 2 ng/mL. If the 
models were used in combination, predicted times of use were accurate for all cases. 

Both models are used frequently in courts of law in many countries to estimate 
elapsed time since last cannabis use in accident and criminal investigations. They 
allow decision makers to answer a corollary question: How accurately can you esti- 
mate the time of last use of cannabis? Officials can use this information to corroborate 
or discount the accused person's story. After estimating the time of last use, the time 
course of performance-impairment data reported in the literature is referenced to sup- 
port a conclusion of possible impairment or lack of impairment. There are many labo- 
ratory, simulator, and on-the-road studies that have shown impairment in tasks required 
for safe driving when individuals have been under the influence of cannabis (66,68), 
especially when cannabis is combined with ethanol (73). 

The onset of impairing effects of THC lags behind the increase in plasma con- 
centration during absorption; then effects remain relatively constant as the concentra- 
tion decreases dramatically because of THC distribution and metabolism (1). This 
concentration-effect relationship, displayed in Fig. 6, is described as a counterclock- 
wise hysteresis. As an example, one can observe two different intensities of effects for 
tachycardia and the visual analog scale for "feel drug" at 50 ng/mL depending on 
whether the individual is in the absorption or distribution phase. Plasma THC concen- 
trations appear to be linearly related to the intensity of effects during absorption and 
elimination, but there is no relationship between concentration and effects during dis- 
tribution. In the case of drivers, it would be rare for authorities to collect a plasma 
specimen prior to the initial distribution phase of THC. After smoking cannabis, 
absorption and distribution are complete in 45-60 minutes. It typically takes longer 
than this to stop the driver, perform a field sobriety test, and transport the driver to a 
site for drawing blood. In the scenario we are considering, it would be important to 
determine the time sequence of events from driving through blood collection to ensure 
that the driver was in the elimination phase. For instructive purposes, we will consider 
that the police officer testified that the time of blood collection was more than 1 hour 
after the driver was stopped and that the driver was under observation during this 
period, precluding further drug use. 



Human Cannabinoid Pharmacokinetics 



215 



VAS Feel Drug Heart Rate 




50 100 150 200 50 100 150 200 

THC ng/mL 

Fig. 6. Visual analog scale for "How strongly do you feel the drug now?" and heart 
rate (BPM, beats per minute) measures for a subject after smoking a 3.55% THC 
cigarette demonstrating a counterclockwise hysteresis for the concentration-effect 
curves. 

Early epidemiological approaches relating cannabinoid plasma concentrations 
to accident risk yielded inconsistent results and were criticized for not including an 
adequate control group of drivers who were on the same roads at similar times and 
who did not have driving accidents (I). An improved approach, responsibility analy- 
sis, independently assigns culpability for the accident and then statistically compares 
the odds ratio or risk that an accident could occur for individuals who had cannab- 
inoids in their system and for those that did not. Culpability analysis proved effective 
for demonstrating performance impairment with alcohol, but was less successful for 
cannabinoids for several important reasons. In many cases blood was not drawn for 
cannabinoid analysis until many hours after an accident or impaired driving incident. 
During this time the concentration of THC in the plasma decreased rapidly, often 
falling below the limits of quantification (LOQs) of the methods used for analysis. In 
many cases, the only analyte identified in plasma was THCCOOH, the inactive 
metabolite with a much wider window of drug detection than parent THC. Some of 
the early studies only reported whether cannabinoids were present in blood or urine, 
not specifying whether measurable THC was found. They used analytical methods 
with high LOQs, i.e., small windows of detection, and were underpowered to identify 
increased risk because of insufficient sample size. Drummer et al. successfully 
employed the empirical approach of culpability analysis and found that the group of 
drivers who had THC present in blood were three to seven times more likely to be 
responsible for their accident than drivers whose blood specimens were negative for 
THC (65,74). Those with THC blood concentrations of 5 ng/mL had the higher prob- 
ability of causing the accident, with a mean odds ratio of 6.8. 

With this body of scientific information, we now can answer the question of 
whether or not marijuana contributed to the driving impairment of the individual in 



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Huestis and Smith 



our example. This individual failed the field sobriety test and had 2 ng/mL of THC in 
his plasma more than an hour after being stopped by the police. In this case, marijuana 
most likely contributed to the performance impairment. The issue of whether or not a 
biological test result alone can be used to document impairment is much more contro- 
versial. In many states and countries, per se laws have been established that state that 
an individual is assumed to be under the influence of cannabis if THC or, in some 
cases, THCCOOH is found in blood, plasma, or, sometimes, urine. The problem of 
drugged driving is a serious public health issue requiring additional research to link 
drug concentrations to ongoing impairment, to determine the best analyte and best 
biological fluid to monitor, and to decide whether administrative cutoff concentra- 
tions are needed. 

What if the accused driver claimed that he might have unknowingly ingested 
food that contained cannabis? If this were true, he might be less culpable and receive 
less punishment. As mentioned, the ratios of 1 1-OH-THC to THC concentrations dif- 
fer following the smoked and oral routes of administration; peak concentrations of 1 1- 
OH-THC after smoking are about 10% that of THC and approximately equal after oral 
administration ( I). If 1 1-OH-THC also was measured in the plasma from the driver in 
our example and its ratio with THC was approx 1:1, this would provide some evidence 
to support his story. 

If we now change venues from the courtroom to the research center, we can 
examine how scientists use plasma concentrations to help understand the mechanisms 
by which cannabinoids affect brain function. Advances in brain imaging using positron 
emission tomography and magnetic resonance imaging have allowed investigators to 
observe changes in CBF as a result of THC administration (12,75-77). A question 
relevant to this area of research might be: How do plasma concentrations of THC 
following administration of cannabis correlate with changes observed in the brain using 
imaging techniques? Mathew et al., who studied 47 subjects who received two differ- 
ent intravenous doses of THC or placebo, found that THC had significant effects on 
global and regional CBF (13). Also, feeling intoxicated accounted for changes in 
regional CBF better than plasma levels of THC. This finding is not surprising in that 
the effects on the brain would be expected to have a more contemporaneous relation- 
ship with related physiological processes in the brain. However, plasma concentra- 
tions provide information about individual differences in processing the same dose of 
cannabis and offer additional information about the metabolites of THC, such as 11- 
OH-THC, which is physiologically active. It would also be interesting to examine 
arterial blood because it has been reported that arterial drug concentrations may be 
more closely related to brain function than venous concentrations (78). Combining 
pharmacokinetic measures with brain imaging following controlled administration of 
cannabis is a new area of research that promises to provide interesting scientific infor- 
mation by examining the process of drug action from ingestion through direct physi- 
ological changes in regions of the brain. 

A related question may be: What information can plasma THC concentrations 
give us about receptor function? Recently, cannabinoid receptors, CB, and CB 2 , and 
endogenous cannabinoid neurotransmitters have been characterized, primarily from 
in vitro and animal studies (79-82). In this line of research, cannabinoids with poten- 



Human Cannabinoid Pharmacokinetics 



217 



tial as pharmacotherapies are often evaluated by first studying their interactions with 
cannabinoid receptors in animals or in vitro, and then examined in human trials. 
SR141716 (named rimonabant), the first CB,-selective cannabinoid receptor antago- 
nist, was shown to block many of the effects of THC in animals (83,84). In a con- 
trolled clinical study of THC s cardiovascular and subjective effects in humans, Huestis 
et al. found that a single 90-mg oral dose of rimonabant antagonized increases in heart 
rate and subjective effects following smoked cannabis (85). It was important to deter- 
mine whether the observed reductions in effects were a result of a receptor-mediated 
pharmacodynamic change or simply a pharmacokinetic interaction reducing the avail- 
able THC. The investigators found that there were no statistically significant differ- 
ences between peak and area-under-the-curve plasma concentrations of THC in the 
placebo and active rimonabant groups. Therefore, blockade of tachycardia and sub- 
jective effects by rimonabant following smoked marijuana was not a result of an alter- 
ation in THC pharmacokinetics. In addition to its role as a pharmacological tool to 
investigate the endogenous cannabinoid system, the antagonist appears to have poten- 
tial efficacy in humans for smoking cessation (86) and weight loss (87); phase III 
trials are ongoing for these medical indications. Other potential therapeutic roles for 
this antagonist are being actively investigated as well. 

Clinical trials are evaluating the efficacy of THC, cannabidiol, and other cannab- 
inoids in the treatment of nausea after cancer chemotherapy, appetite loss, multiple 
sclerosis, and neuropathic pain ( 16). A common clinical question might be: How will 
monitoring plasma cannabinoid concentrations aid clinical management of these 
patients? As with any new pharmaceutical preparation, it is necessary to study the 
drug's pharmacokinetics to more clearly understand required doses, frequency of dos- 
ing, contributions of metabolites to effects or toxicity, elimination profiles, and metabo- 
lism and excretion in different populations, including newborns, children, ethnic groups, 
diseased individuals, and the elderly. For example, one must determine the median 
effective dose, ED 50 , for these populations to assist clinicians who must prescribe doses 
that will be efficacious but avoid toxicity. 

Another concern of clinicians prescribing medications is abuse liability. It has 
been shown that the route of administration affects the abuse liability of a drug (88). 
As discussed above, inhalation of smoked cannabis, which results in rapid increases 
in THC concentrations, can be an effective way for individuals to titrate their THC 
dose, but may increase its abuse liability. Most clinical trials are evaluating oral, sub- 
lingual, or inhaler formulations to better control dose and reduce toxic side effects 
from smoking. This is expected to reduce the abuse liability as well. Well-designed 
clinical trials that include pharmacokinetic analyses in tandem with clinical assess- 
ment of patients are needed to establish the efficacy and pharmacokinetics of these 
new preparations and new delivery routes. 

7.2. Urine 

Many governmental and private organizations in the United States employ drug 
testing as part of their drug use-prevention programs. Urine is the biological matrix 
most commonly tested to identify individuals who use drugs. In 2003 it was estimated 
that more than 20 million urine specimens were collected for drug testing in United 



218 



Huestis and Smith 



States programs. Drug testing is also an important objective outcome measure of drug 
treatment, drug research investigating efficacy of new behavioral therapies, criminal 
justice, military programs, and emergency, pediatric, and geriatric medicine. A com- 
mon example is judicial programs that routinely collect urine from individuals on 
parole. Individuals committing crimes and having a positive urine drug test may be 
placed in treatment while on parole if the judge believes that drug use contributed to 
the crime. Parolees are ordered to attend a rehabilitation program, are given a short 
period of time to eliminate previously self-administered drugs from their bodies, and, 
as a condition of continued parole, must discontinue use of prohibited drugs. To en- 
sure compliance, treatment managers routinely have the parolee donate urine speci- 
mens, and if there is a positive urine test indicating new drug use, the donor may be 
sent to prison. This example sets the stage for an important social question. If a pa- 
rolee who was a chronic marijuana user had a sequential set of urine tests during his 
first week of rehabilitation with decreasing concentrations of THCCOOH from 1000 
ng/mL down to 100 ng/mL by the end of the week, and then donated a urine specimen 
with a concentration of 150 ng/mL, does this increase in urine concentration indicate 
new use in violation of his parole? 

Figure 4 shows a typical urinary excretion profile for THCCOOH in an infre- 
quent marijuana user following smoking of a single marijuana cigarette. As mentioned 
previously, there is great inter- and intrasubject variability in the urinary excretion of 
cannabinoids. Many investigators have published studies showing that in a sequential 
series of urine specimens from individuals who abstained from smoking cannabis, 
there can occasionally be urine specimens that have higher concentrations of THC- 
COOH than previous samples (89-91). This could be a result of residual excretion of 
drug that has been stored in the body following chronic cannabinoid use. Most of 
these increases in concentration appear to be related to individuals' hydration states 
that are determined by fluid intake, environmental temperature, levels of activity, dis- 
ease states, and a multitude of other variables. Urine may be diluted and drug concen- 
trations reduced as a result of ordinary variations in daily activity or purposeful attempts 
to adulterate the sample by specimen dilution, achieved by simply drinking large quan- 
tities of fluid. In controlled studies of cocaine and cannabinoid administration fol- 
lowed by consumption of different amounts of liquids, investigators were able to 
demonstrate large reductions in urine drug concentrations. In many cases, results fell 
below cutoff concentrations for a positive test (92). 

Manno et al. first suggested that urinary THCCOOH could be normalized to 
urinary creatinine concentration to account for specimen dilution (91). They recom- 
mended a quotient cutoff of > 1.5 to identify new drug use. Huestis and Cone addressed 
this problem by examining more than 1800 urine specimens collected following con- 
trolled THC administration (89). They found that the greatest accuracy (85.4%) in 
predicting new cannabis use occurred when paired specimens collected at least 24 
hours apart had a quotient of >0.5 for the [THCCOOH]/[creatinine] in specimen 2 
divided by the [THCCOOH]/[creatinine] for specimen 1. If the 1.5 ratio was used, as 
proposed by Manno, almost 30% of the cases of new drug exposure would be missed. 
Figure 4 shows that normalizing the THCCOOH concentration to creatinine concen- 
trations makes the excretion pattern more predictable, i.e., it has fewer abrupt changes 
in the exponential decrease. 



Human Cannabinoid Pharmacokinetics 



219 



The Huestis and Cone study examined infrequent cannabis users and did not 
address excretion patterns that one would expect from chronic use. As mentioned, 
chronic users take longer than infrequent users to eliminate marijuana metabolites. 
This is a result of the disposition of THC into poorly perfused tissues such as fat. With 
chronic cannabis use, THC concentrations in these poorly perfused compartments 
increase, forming less accessible depots of THC in the body. Hunt and Jones demon- 
strated that the slow return of THC from these depots into the plasma was the rate- 
limiting step in the terminal elimination of THC from the body (36). Fraser and Worth 
studied a group of 26 chronic marijuana users, testing both the Manno and Huestis 
criteria for new use and had a false-negative rate of 7.4% with the Huestis guideline 
and 24% with the Manno rule (93). They extended the study to include 37 chronic 
marijuana users with at least 48 hours between specimens; with the >0.5 cutoff, new 
drug use was identified in 80-85% of cases (94). Of course, the smaller the ratio used, 
the greater the potential for false-positive results. The reasons for conducting the urine 
test, i.e., treatment or parole, and the impact of the results on the donor guide the 
choice of which ratio to apply. 

Based on this valuable scientific information, we can answer the question about 
whether the individual on parole in our example had smoked marijuana between 
donating the specimen containing 100 ng/mL THCCOOH and the specimen with 
150 ng/mL THCCOOH. The answer is that we cannot tell if he used cannabis in vio- 
lation of his conditions for parole. Additional information is needed to differentiate 
between new cannabis use and residual drug excretion. This spike in urine concentra- 
tion would not be unusual for an individual who had complied with his treatment 
protocol. If the treatment center had collected the specimens at least 24 hours apart 
and had measured creatinine concentrations, we would have additional information to 
provide a more definitive answer. If the outcome of the evaluation could be used to 
place the individual, who was a former chronic cannabis user, in prison for continuing 
use after entering his rehabilitation program, the higher ratio of 1.5 might be a better 
choice for evaluating his urine tests. This would achieve better specificity, rather than 
sensitivity. In addition, more frequent monitoring may be useful if urine specimens 
are being collected more than 48 hours apart. 

7.3. Oral Fluid 

Oral fluid is composed of saliva and secretions from the nasopharyngeal area 
and mouth. Mechanisms of drug entry into oral fluid are not fully understood. Scien- 
tists have determined that passive diffusion from blood and tissue depots and direct 
entry into oral fluid following smoked, oral, sublingual, or snorted routes of drug 
administration are the primary sources. In rare cases (e.g., lithium), active transport 
mechanisms also may contribute. Some of the factors affecting how much drug enters 
oral fluid from the blood are the lipophilicity of the drug, the degree of plasma protein 
binding, the drug's pK a , and pH differences between blood and oral fluid. In general, 
if the drug is not extensively bound to plasma proteins, is lipophilic, and is present in 
an unionized state, passive diffusion is the primary mechanism for drug entry into oral 
fluid. The lower pH in oral fluid as compared with blood can result in ion trapping of 
drugs with a higher pK a (e.g., codeine), which has concentrations three to four times 



220 



Huestis and Smith 



I 



Intoxication 
Impairment 
Under Influence 
Blood 

Oral Fluid I r 

Urine 
Sweat 

Hair 



Minutes Hours Days Weeks Months Years 



Fig. 7. General drug effects and detection time ranges in various matrices following 
occasional cannabinoid use. (Personal communication from Edward J. Cone, PhD.) 




higher in oral fluid (95). In general, detection times for drugs in oral fluid range from 
a few hours to 1 or 2 days following use (see Fig. 7). 

There are few data on the disposition of cannabinoids in oral fluid following 
controlled cannabis administration. Scientists have known that THC is present in oral 
fluid since the 1970s (96,97), and in the 1980s Gross et al. found that they could detect 
THC in saliva with RIA for 2-5 hours in 35 subjects who smoked one marijuana 
cigarette containing 27 mg THC (98). However, the specificity of this assay was low, 
with frequent false-positive results. One of the first studies to examine cannabinoid 
concentrations in oral fluid after intravenous administration of radiolabeled THC found 
no radioactivity in the oral fluid, indicating that THC in oral fluid after smoking was a 
result of direct contamination of the oral mucosa and oral fluid in the mouth, and not 
from passive diffusion from plasma (99). Another study examined oral fluid follow- 
ing the smoking of 1.75 and 3.55% marijuana cigarettes by six participants (100). 
Specimens were collected by expectoration before and periodically up to 72 hours 
after smoking. All specimens were analyzed for cannabinoids using specific RIAs for 
THC and THCCOOH, with cutoff concentrations of 1.0 and 2.5 ng/mL, respectively. 
THC was detected in oral fluid for up to 24 hours after the higher dose. No specimens 
were positive for THCCOOH by RIA. In addition, one participant's specimen set was 
analyzed by GC/MS for THC, 11-OH-THC, and THCCOOH with LOQs of 0.5 ng/ 
mL. This analysis confirmed that no measurable 11-OH-THC or THCCOOH was 
present throughout the time course in any of the oral fluid specimens. Niedbala et al. 
studied 18 subjects who were administered single doses of marijuana by smoked (20- 
25 mg) or oral (20-25 mg) routes (101). Urine and oral fluid specimens (Intercept 
collection device, OraSure Technologies, Inc., Bethlehem, PA) were collected at in- 
tervals up to 72 hours. Oral fluid was screened with a cannabinoid enzyme immunoas- 



Human Cannabinoid Pharmacokinetics 



221 



say (Intercept Micro-Plate EIA, OraSure Technologies, Inc.) with a cutoff concentra- 
tion of 1.0 ng/mL and confirmed for THC by GC tandem MS, cutoff concentration of 
0.5 ng/mL. Urine was screened by cannabinoid immunoassay (Abuscreen Online, Roche 
Diagnostics, Inc., Indianapolis, IN) and GC-MS for THC-COOH, cutoff concentra- 
tions of 50 and 15 ng/mL, respectively. Oral fluid specimens tested positive following 
marijuana smoked consecutively for average periods of 13 hours. The average time of 
the last positive test was 31 hours. There was great individual variation, with one 
subject having the last positive specimen at 2 hours and another at 72 hours. The 
decrease in oral fluid THC concentrations during the first 2 hours appeared to parallel 
those published by others for plasma THC, but no plasma was collected in this study 
for direct comparison. Urine specimens were consecutively positive following smok- 
ing for an average of 26 hours. The average time for the last positive reading was 42 
hours with ranges up to 72 hours, the last collection. In the oral ingestion study, each 
of three subjects ate one brownie that had been cooked with plant material containing 
20-25 mg of THC. THC was present in oral fluid following this method of oral inges- 
tion, but concentrations peaked at 1-2 hours, were low, 3-5 ng/mL, and declined rap- 
idly to negative, typically at 4 hours. 

In recent studies oral fluid has been collected in a wide variety of devices designed 
by different manufacturers. Unfortunately, the recovery of cannabinoids from these 
devices is frequently unknown, a fact that significantly affects the devices' sensitivity 
in detecting cannabinoid use. Another problem area is the immunoassay reagent used 
to screen oral fluid specimens for cannabinoids. Many of the manufacturer's reagents 
target THC-COOH in their antigen-antibody reactions, making the sensitivity of these 
tests for cannabinoid exposure unacceptably low. Kintz et al. examined oral fluid 
(Salivette), blood, forehead wipes, and urine from 198 injured drivers and found 22 
positive by urine testing for THC-COOH (102). Fourteen of these patients were also 
positive for THC in oral fluid, with no specimens positive for 11-OH-THC or THC- 
COOH at the limits of detection for their method. Samyn et al. collected urine from 
drivers who failed field sobriety tests at police roadblocks (103). For drivers who had 
a positive urine test, blood specimens were collected and, following informed con- 
sent, oral fluid (Salivette) and sweat specimens were collected. Oral fluid specimens 
and plasma were collected from 1 80 drivers and analyzed by GC-MS with cutoff con- 
centrations of 5.0 and 1.0 ng/mL, respectively. The predictive value of oral fluid com- 
pared with plasma was 90%. In a different approach, Cone et al. examined 77,218 oral 
fluid specimens submitted to a large drug-testing laboratory (104). Using an oral fluid 
screening cutoff concentration for cannabinoids of 3 ng/mL and a confirmation THC 
cutoff concentration of 1.5 ng/mL, they found a cannabis positive rate of 3.22%, which 
was similar to the positive rate of 3.17% for large urine drug-testing laboratories using 
federally mandated cutoff concentrations. These studies have shown that measure- 
ment of THC in oral fluid compares favorably with sweat and urine testing for detect- 
ing cannabis use. Others have not found a good correlation between cannabinoid tests 
for oral fluid and other body fluids ( 105-109). Some of this variability in performance 
may be related to differences in cutoff concentrations, different screening specifici- 
ties, binding of THC by the collection devices, and large intersubject differences of 
cannabinoid concentrations in biological fluids. The Substance Abuse Mental Health 



222 



Huestis and Smith 



Services Administration, Department of Health and Human Services (SAMHSA), which 
regulates federal workplace drug testing in the United States, is currently proposing a 
screening cutoff of 4 ng/mL for cannabinoids and a confirmation cutoff of 2 ng/mL 
THC for oral fluid (110). 

Menkes et al. reported that the logarithm of salivary THC concentrations corre- 
lated with subjective effects and heart rate (111). Based on all of the available data 
and the ease of collection of oral fluid, many states and countries are considering the 
use of oral fluid testing for identification of drugged drivers. A large-scale roadside 
evaluation of the effectiveness of oral fluid monitoring for identifying drug-impaired 
drivers is being conducted currently in Europe and the United States (112,113). 

Some organizations are interested in oral fluid testing of employees before be- 
ginning safety-sensitive work, because collection is easy and devices can give a quick 
screening result on-site. We will take this setting for a question regarding oral fluid 
testing. If a woman reports to a worksite to operate the reactor in a nuclear power 
station and her oral fluid screens positive for THC, is the manager justified in assign- 
ing her less sensitive duties until the test can be confirmed by a more specific method? 
If the woman had signed a pre-employment agreement not to use impairing drugs 
within 24 hours of reporting to work, did she violate her agreement, an act that could 
result in termination of her employment? The easy answer is that we cannot prove that 
she used cannabis based on a screening test. The result must be confirmed by a second 
method based on a different scientific principle of identification; however, it is in- 
structive to examine the reliability of the result because many organizations would 
remove this person from safety-sensitive duties based on a positive screening test. The 
suspect employee would be returned to normal duties if the presumptive positive test 
was not confirmed by further laboratory testing. If the nuclear power facility had a 
drug policy outlining the terms and conditions for drug testing and ramifications of a 
positive screening and confirmation test and the woman had been informed of these 
regulations, then removal from a safety-sensitive position is a prudent action to take. 
Can we determine when the cannabinoid exposure occurred to answer the second part 
of the question? As mentioned above, with an oral collection device and screening and 
confirmation cutoffs of 1 and 0.5 ng/mL, respectively, Niedbala et al. found typical 
detection times of less than 24 hours, but some subjects produced a positive oral fluid 
specimen 72 hours after smoking (101). If the confirmatory test is positive and the 
cutoff concentrations and methodology are the same as those used in the controlled 
clinical study, we may be able to limit the window of drug exposure to within the past 
few days. It would be important to know the collection device and the laboratory's 
procedures, in particular the cutoff concentrations used. Unfortunately, data from well- 
controlled clinical studies to aid our interpretation are limited. Oral fluid collection 
devices and testing methodologies differ, and their performance may not have been 
evaluated in controlled studies. We cannot state definitively that she violated her agree- 
ment and used cannabis within 24 hours prior to reporting for work. 

There is another interesting point to consider in the interpretation of oral fluid 
results. Suppose the woman states that she did not use illegal drugs but that she was 
passively exposed to marijuana smoke when her boyfriend and two of his friends 
smoked cannabis in her small kitchen. Could this explain the positive oral fluid test? 



Human Cannabinoid Pharmacokinetics 



223 



Although there are limited data in the literature, Niedbala et al. reported that two sub- 
jects who did not smoke cannabis but were in the room when others smoked had some 
positive screening but no confirmed oral fluid cannabinoid tests (101). Subsequent 
studies that are not yet published but were presented at the International Association 
of Forensic Toxicologists meeting in 2003 in Melbourne, Australia, and at a confer- 
ence for Medical Review Officers (personal communication from S. Niedbala of 
OraSure Technologies, Inc.) conveyed the potential for passive exposure to marijuana 
smoke resulting in positive screening and confirmation tests. These results occurred 
when considerable smoke was present in small spaces, and oral fluid specimens were 
negative within 45 minutes of the end of exposure. This situation may be analogous to 
research that documented the possibility of a positive urine drug test following exten- 
sive passive exposure to marijuana smoke in a sealed experimental room (114). Al- 
though a positive test was produced in this experimental setting, participants complained 
of noxious smoke and irritation to the eyes. Other research conducted under more 
realistic passive smoke conditions indicated that production of a positive urine test 
with currently mandated federal guideline cutoffs is highly unlikely (115,116). A pas- 
sive inhalation defense has rarely been accepted for a positive urine cannabinoid test. 
Additional research is needed to characterize the potential for positive oral fluid can- 
nabinoid test from passive exposure. Perhaps the selection of appropriate oral fluid 
screening and confirmation cutoff concentrations can eliminate a positive oral fluid 
test from passive exposure. We lack appropriate data to answer the question of passive 
exposure of oral fluid at this time and must admit that additional controlled drug ad- 
ministration and naturalistic studies of drug in oral fluid are needed before we can 
definitively address the woman's claim of passive exposure. 

7.4. Sweat 

The substance collected for sweat testing is actually a combination of secretions 
onto the skin. Cannabinoids and other drugs are transported into sweat by diffusion 
from blood and other depots. Sweat from eccrine glands and sebum from apocrine 
sweat glands and sebaceous glands are the main constituents. Eccrine glands are lo- 
cated throughout the body near the surface of the skin, and the sweat they produce is 
aqueous, contains salts, is usually in the pH range of 4.0-6.0, and is produced at vari- 
able rates with an average of approx 20 mL per hour. Apocrine sweat glands are 
located in the shaft of the hair follicle and excrete a substance that is viscous, cloudy, 
and rich in cholesterol, triglycerides, and fatty acids. This secretion mixes with sebum, 
a similar viscous liquid rich in triglycerides and long-chain esters, from sebaceous glands 
in the hair bulb region. Sweat and sebum mix to form an emulsion on the skin surface. 
When sweat is collected for testing, this mixture is the substance absorbed onto patches. 
Once drugs diffuse into the glands, it is believed that eccrine sweat transports the drugs 
to the surface of the skin within hours, the known time frame for sweat excretion. 

Two commercial collection devices are the most commonly used, the PharmChek® 
patch (PharmChem Laboratories, Dallas, TX), and Drugwipe® (Securetec, Ottobrunn, 
Germany). Some investigators have also used absorbent pads and wiped the forehead 
or other regions of the body, and then extracted absorbed substances from the pad. 
PharmChek, the only US Food and Drug Administration-approved collection device 



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for drugs of abuse testing, has an absorbent pad covered by a tamper-resistant adhe- 
sive that is porous enough to allow the skin to breathe but protects against external 
contamination. Some investigators believe that it is possible to contaminate the sweat- 
collection pad through the adhesive cover or by insufficient cleaning of the skin sur- 
face before placement of the patch (117,118). These devices provide a cumulative 
record of drug use over the wear time for the patch, usually 7 days, in many instances 
increasing the sensitivity of drug detection over other monitoring techniques. The 
Drugwipe device, which employs an absorbent material to wipe the skin and an immu- 
nochemical test strip for drug detection, has been evaluated in some studies 
(102,107,119). 

There are few published reports of cannabinoid concentrations in sweat follow- 
ing drug use. One issue is that the collection device does not accurately measure the 
volume of sweat collected, analogous to the case with oral fluid collection with a 
device rather than by expectoration. Therefore, scientists report the amount of drug 
collected per patch, not as a concentration of drug in sweat. Another issue is that the 
amount of sweat excreted and collected varies based on the amount of exercise and 
ambient temperature. There also are insufficient data to evaluate recovery of cannab- 
inoids from the patch during sample preparation. Kintz et al. collected urine, oral 
fluid, and sweat (Drugwipe) samples from injured drivers, and then tested each by 
immunoassay and GC/MS. Of 22 patients who had a positive urine test, 16 also had a 
positive sweat test ( 102). The amounts of THC in sweat ranged from 4 to 152 ng per 
pad, with no detection of 1 1-OH-THC or THC-COOH in any specimen at the limit of 
detection of the method. Samyn et al. collected blood, urine, oral fluid, and sweat (by 
wiping the forehead with a fleece moistened with isopropanol) from 180 drivers who 
failed a field sobriety test (103). They reported a positive predictive value compared 
to plasma testing of 80% for the cannabinoid sweat test using GC/MS testing at cutoff 
concentrations of 5 and 1 ng/mL, respectively. In an earlier study, Samyn and Haeren 
found a high number of false-negative and some false-positive cannabinoid sweat testing 
results using a Drugwipe device (107). SAMHSA has proposed guidelines for sweat 
cannabinoid testing using the PharmChek patch and a wear period of 7 days with a 
screening cutoff of 4 ng THC per patch and a confirmation cutoff of 1 ng THC per 
patch (110). 

One application of sweat testing is monitoring drug use in individuals in drug 
rehabilitation programs. A tamper-proof patch is often placed on the upper arm or 
back for 7 days, the collection pad is removed, drugs are eluted from the pad, and the 
extract is tested for the presence of drugs. Suppose that a sweat patch were applied to 
an individual who entered a drug rehabilitation program after providing a negative 
urine test and the patch was removed 7 days later for testing. If a THC concentration 
of 4 ng/patch was obtained, does this indicate that he had used cannabis after entrance 
into the program in violation of his treatment contract? 

Based on the published information available, it is most likely that THC detected 
in the patch indicates cannabis use after he entered the program, assuming that the 
skin was properly cleaned before applying the patch and that handling procedures 
avoided contamination during patch removal and storage. However, no published stud- 
ies have related urine THC-COOH concentrations to sweat THC patch results, mak- 



Human Cannabinoid Pharmacokinetics 



225 



ing it difficult to state with certainty that the results were a result of new cannabis use. 
It is expected that if the THC in the sweat patch indicated drug usage just before patch 
application, the urine drug test also would have been positive. It might be that drug 
depots in the skin of heavy, chronic cannabis users could continue to excrete THC in 
sweat after the individual abstains from further drug use, although this hypothesis has 
never been tested. It is also possible that cannabinoids could remain in sebum longer 
than in urine since sebaceous glands often release sebum when they lyse, a process 
that can take up to 2 weeks. Therefore, it is possible that the THC found in the patch 
represented drug use before entering the program. Additional controlled drug admin- 
istration and naturalistic studies of drug excretion in sweat are needed to improve the 
interpretation of cannabinoid sweat tests. 

7.5. Hair 

Drugs enter hair through several diffusion mechanisms; from the blood into the 
highly perfused bulb of the hair shaft, from sebum and sweat along the hair root and 
shaft, and from direct contact with drug in the environment (120). More basic drugs 
are bound primarily to eumelanin through ionic interactions; little drug binds to 
pheomelanin ( 121 ). This difference in binding properties is one explanation for higher 
concentrations of basic drugs in dark colored hair, which has higher eumelanin con- 
tent, than in light-colored hair, which may have primarily pheomelanin or less total 
melanin (122,123). 

In general, following a single dose, basic drugs that enter hair can be detected by 
the most commonly used techniques 3-7 days after drug administration, peak in 1-2 
weeks, and decrease thereafter (124-126). Hair grows at a rate of about 1 cm per 
month, providing an opportunity to segment hair to determine periods of drug use 
over time. Studies relating time of drug use with presence in specific hair segments 
have had inconsistent results. Kintz et al. have utilized segmental hair analysis to 
indicate the time of drug exposure in drug-facilitated sexual assault (127), and others 
have used measurement of antibiotics in hair to monitor hair growth and tie the pres- 
ence of these drugs to known times of drug administration (128). Other investigators 
administered deuterated cocaine and showed that the presence of this drug was not 
restricted to the appropriate hair segments but was found throughout the hair shaft 
(124). These data are consistent with the theory that drug in sweat may bathe the hair 
shaft and deposit drug along the length of the hair follicle. Many drugs are well pro- 
tected by hair and may be detected hundreds of years after the death of an individual 
(129,130). Although questions remain about the different mechanisms of drug incor- 
poration, in general, drug concentrations in hair appear to be somewhat dose related, 
even though the correlation is not well defined ( 131 ); that is, higher and more frequent 
drug use is usually reflected in higher hair concentrations (126,132). However, most 
of our knowledge about drug concentrations in hair is derived from studies of basic 
drugs such as cocaine, amphetamines, and opiates. There are almost no data from 
controlled cannabinoid administration studies to help us in our interpretation of can- 
nabinoid hair tests. This is especially important because THC is a more neutral com- 
pound and is not thought to bind to hair through the ionic mechanisms that are important 
components of incorporation of basic drugs. 



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Furthermore, THC is present in cannabis smoke, and external contamination of 
hair through this mechanism is a concern. Thorspecken et al. contaminated hair with 
cannabis smoke, and then tried two different wash techniques to remove THC (133). 
Their methanol and methylene chloride wash method removed most of the THC from 
hair that was a result of contamination. A dodecyl sulfate wash removed external con- 
tamination from all hair samples tested. Scientists have recommended testing for THC- 
COOH in hair as another way to address the issue of external contamination with 
THC; however, the concentrations of THC-COOH in hair are in the low pg/mg range, 
usually requiring tandem MS or special chemical ionization MS analytical techniques 
( 134). These instruments may not be available to many analytical laboratories because 
of the high cost of the equipment, yet the validity of testing only for THC is a highly 
contested issue in forensic toxicology. The concern for reducing the possibility of 
external contamination has motivated SAMHSA to propose guidelines that set the 
cutoff concentrations for cannabinoids in hair at 1 pg/mg of cannabinoids for screen- 
ing and 0.05 pg/mg of THC-COOH for confirmation testing. Test results must equal 
or exceed these limits before one may report a hair specimen positive when collected 
in a workplace program (110). 

Another complication in determining a drug's disposition into hair and expected 
values after use is the variability in analytical procedures among laboratories. Differ- 
ent wash procedures are used to remove external contamination, different digestion 
procedures are employed to facilitate extraction of the drug, and different analytical 
procedures and instruments are utilized to identify and quantify drugs. Our under- 
standing of recovery of cannabinoids incorporated into authentic users' hair is poor. 
Scientists can measure the efficiency of extraction methods when cannabinoids are 
spiked into hair, but this technique probably does not adequately reflect the extraction 
of drug incorporated into hair following cannabis use. Cannabinoid measurements are 
further complicated by the very low concentrations of drug in hair. Jurado et al. found 
THC and THC-COOH concentrations in hair of cannabis and hashish users that ranged 
from 0.06 to 7.63 ng/mg and 0.05 to 3.87 ng/mg, respectively (135). Cirimele et al. 
found lower concentrations for THC and THC-COOH of 0.26-2. 17 and 0.07-0.33 ng/mg 
of hair, respectively, in 43 subjects who had died from fatal heroin overdoses ( 134, 136). 
Other investigators have found much lower concentration ranges, often in the pg/mg 
range (137). Testing differences and difficulties in analyzing very low concentrations 
often result in a wide range of reported concentrations, as documented by Jurado et al. 
in a quality control study that had 18 laboratories analyze the same lot of hair samples 
and found a 93% coefficient of variation (138). 

Let us consider the question regarding the individual accused of using cannabis 
before driving that resulted in a plasma THC concentration of 2 ng/mL. Suppose this 
man claimed that someone put the cannabis in his food just before driving and that he 
had not knowingly used cannabis in the past year. If a hair specimen were submitted 
for testing to support his contention and the analysis for cannabinoids were negative, 
could the man legitimately use this information to support his claim that he did not 
smoke cannabis during the past year? To answer this question, we must first under- 
stand the pharmacokinetics of cannabinoid disposition into hair. How extensive was 
the laboratory's wash procedure, what analytes were targeted, what laboratory proce- 



Human Cannabinoid Pharmacokinetics 



227 



dures were used, and what were the cutoff concentrations? The cutoff concentrations 
for the laboratory procedure are critical because for many laboratories cannabinoid 
cutoff concentrations are close to the limit of detection. If we find that the laboratory 
procedures were valid and cutoff concentrations similar to those recommended by 
SAMHSA, we can make some assessments. For example, the driver might not have 
been a chronic user of cannabis. However, we cannot say that the negative hair test 
supports his assertion that he never used cannabis during the past year except 
unknowingly when someone put cannabis in his food the day he was arrested. The low 
concentrations of THC and metabolites in hair and the lack of published dose-response 
data following controlled administration of cannabis will not allow us to answer the 
question. The best answer to the original question is that the negative hair result is 
supporting evidence that he is not a chronic cannabis user. 

Let us suppose that the test had been positive. Could the prosecution use this 
information to support their claim that the man had used cannabis prior to this most 
recent incident, indicating a lie that would reflect poorly on his integrity and make his 
story about unknowing ingestion less credible? Once again the procedures and cutoff 
concentrations are important, but for instructive purposes we will assume they are 
reliable and similar to the proposed guidelines. As mentioned, we do not have data 
from studies following controlled administration of cannabis to assist in interpreting 
the positive hair test result. However, the studies on cocaine, codeine, and other basic 
drugs show that drugs or metabolites do not appear for at least 3-7 days when the hair 
is cut, not plucked, and usually appear later if the hair testing method has removed 
external contamination from sweat. If THC follows similar kinetics, its presence, along 
with the presence of other cannabinoids such as cannabinol, cannabidiol, and THC- 
COOH, would support the contention that the man had used cannabis, but not specifi- 
cally on the day of his arrest. What about the possibility of external contamination? 
The presence of THC-COOH makes external contamination less likely because it 
indicates that the drug was actually metabolized by the body. There are no data to 
indicate that THC-COOH is present in cannabis smoke. Also, if appropriate wash 
procedures were used, external THC contamination would be less likely and the evi- 
dence of drug use stronger (133). The answer to the original question would be that 
the presence of cannabinoids and specifically THC-COOH in the man's hair is sup- 
porting evidence that he used cannabis prior to the day he was stopped for driving 
erratically; this evidence would not lend support to a case of impairment at the time of 
arrest. 

8. Final Thoughts 

The information in this chapter demonstrates that the disposition and time course 
of cannabinoid analytes into different biological fluids and tissues is critical for inter- 
preting drug test concentrations and answering related scientific and social questions. 
Each matrix has advantages and limitations. Blood or plasma interacts with cells 
throughout the body, including the central nervous system; cannabinoid concentra- 
tions in these biofluids more closely relate to drug effects, but the window of drug 
detection is usually limited to hours. Urine, a depot for waste, has an analysis time 



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frame of days for detecting drug use and provides important information about drug 
metabolism, but concentrations of urine cannabinoids are difficult to relate to effects 
of the drug. Oral fluid appears to absorb THC directly from contact with cannabis and 
is a convenient fluid for detecting recently smoked cannabis. Concentrations of drugs 
in sweat are difficult to determine as a result of problems obtaining an accurate vol- 
ume of excreted sweat, but detecting drugs in sweat patches or wipes has important 
applications for detecting drug use occurring over 1-2 weeks. Drugs appear to be 
more stable in hair and have larger windows of detection, from weeks to years. Analy- 
sis of each of these matrices offers unique scientific information. Knowledge of the 
disposition of drugs and metabolites in these fluids and tissues after controlled drug 
administration provides a powerful pharmacokinetic database for scientists who are 
called upon to give science-based answers to important questions that have a major 
impact on our society. 

A CKNOWLED GMENTS 

The authors wish to thank Beverly Cepl, Karen Schaeffer, David Darwin, Deborah 
Price, and Insook Kim, Ph.D., for providing assistance with the reference material for 
the manuscript. 

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Chapter 10 



Medical and Health Consequences 
of Marijuana 

Jag H. Khalsa 

1. Introduction 

Marijuana is the most frequently used illegal drug in the world today. Some 146 
million people, or 3.7% of the population 15-64 years of age, consumed cannabis in 
2001-2003 (1). In the United States, 95 million Americans over the age of 12 have 
tried marijuana at least once. In 2002, an estimated 15 million Americans had used the 
drug in the month before a survey (2), representing 6.2% of the population age 12 
years and older. Marijuana was used either alone or in combination with other drugs 
by 75% of the current illicit drug users. Approximately 2-3 million new users of mari- 
juana are added each year, with about 1.1% becoming clinically dependent on it (3). 
In the case of young people, according to a recent survey of high school students 
known as Monitoring the Future, supported by the US National Institute on Drug Abuse 
(NIDA) and conducted yearly, at least 19% of 8th graders had tried marijuana at least 
once and 18% of 10th graders were "current" drug users (i.e., had used the drug within 
the past month before the survey). Among 12th graders, nearly 48% had tried mari- 
juana at least once, and approx 21% were "current" marijuana users (4). Marijuana 
use by young people has increased or decreased at various times during the last decade, 
possibly as a result of its potency, which has been on the rise, although nonsignifi- 
cantly — from a 3% concentration of A 9 -tetrahyrocannabinol (THC; marijuana's active 
chemical constituent) in 1991 to 4.4% in 1997 — possibly because of changes in the 
perceptions of youths about marijuana's dangers or other unknown factors. Research 
suggests that marijuana use usually peaks in the late teens to early 20s, and then declines 
in later years (5). 



From: Forensic Science and Medicine: Marijuana and the Cannabinoids 
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey 



237 



238 



Khalsa 



Marijuana use has been reported to cause adverse psychosocial and health con- 
sequences. The psychosocial consequences of marijuana use — such as dropping out 
of school, poor school performance, antisocial and other behaviors of youth — have 
been the subjects of many publications. Therefore, this chapter presents current research 
on the medical and health consequences of marijuana use (6), including the adverse 
effects on the immune, cardiopulmonary /respiratory, hepatic, renal, endocrine, repro- 
ductive, and central nervous systems, genetic aspects, and general health. The chapter 
also includes a brief discussion of the treatment of marijuana dependence, the carcino- 
genic potential of marijuana, and motor effects with respect to driving performance 
and traffic accidents. 

Marijuana use is associated with a myriad of pharmacological effects that may 
be attributable to THC as well as to some of its less psychoactive chemical constitu- 
ents, known as cannabinoids and endocannabinoids: the latter have been observed in 
the central and peripheral nervous systems, as well as in the immune, cardiovascular, 
and reproductive systems. However, the physiological roles of these cannabinoids have 
not yet been fully defined. Evidence suggests that endocannabinoids are involved in 
the amelioration of pain, blocking of working memory, enhancement of appetite and 
suckling, cardiovascular modulation including blood pressure lowering during shock, 
and embryonic development. They may also be of importance in psychomotor control 
and in the regulation of some immune responses (7). 

The acute effects of marijuana use may include euphoria, anxiety, and panic, 
especially in naive users; impaired attention, memory, and psychomotor performance; 
perceptual alterations; intensification of sensory experiences, such as eating, watch- 
ing films, listening to music; increased risk of psychotic symptoms, especially among 
those who are already vulnerable because of a personal or family history of psychia- 
tric/psychological problems (8); and possibly increased risk of motor accidents, espe- 
cially if used concomitantly with alcohol (9). 

2. Immune System Effects 

Marijuana impairs cell-mediated and humoral immunity in rodents and decreases 
resistance to bacterial and viral infections; noncannabinoids in cannabis smoke impair 
alveolar macrophages (10). However, the few nonhuman animal studies that found 
adverse immunological consequences of marijuana have not been replicated in humans 
(11). There is no conclusive evidence to suggest that use of marijuana impairs immune 
function, as measured by number of T-cell lymphocytes, B-cell lymphocytes, mac- 
rophages, or levels of immunoglobulin (11). No epidemiological data or data from 
case reports suggest that marijuana is immunotoxic or that it increases the risk of 
exacerbating other bacterial or viral diseases in marijuana users. Two recent prospec- 
tive studies of HIV infection in homosexual men showed no clear association between 
marijuana use and increased risk of progression to AIDS (12,13). Kaslow and col- 
leagues (13) conducted a prospective study of progression to AIDS among HIV-posi- 
tive men in a cohort of 4954 homosexual and bisexual men. Marijuana use did not 
predict an increased rate of progression to AIDS among men who were HIV positive, 
nor was marijuana use related to changes in a limited number of measures of immuno- 



Medical and Health Consequences of Marijuana 



239 



logical functioning. Thus, although persons infected with HIV have been advised to 
avoid marijuana, this advice appears to be reasonable as a general health precaution. 
The fact that Marinol (dronabinol, THC) has been approved by the US Food and Drug 
Administration for the treatment of anorexia associated with weight loss in patients 
with AIDS and the nausea and vomiting associated with cancer chemotherapy shows 
that Marinol does not impair the immune system significantly and does not exacerbate 
bacterial or viral infections. It is not known whether studies have been conducted in 
this area. 

3. Cardiopulmonary/Cardiorespiratory Effects 

Marijuana use is associated with serious cardiovascular consequences. Acutely, 
marijuana increases heart rate, supine blood pressure, and, after higher doses, orthos- 
tatic hypotension; it increases cardiac output, decreases peripheral vascular resistance, 
and dose-dependently decreases maximum exercise performance. With prolonged 
exposure, supine blood pressure falls, orthostatic hypotension disappears, blood vol- 
ume increases, heart rate slows, and circulatory responses to exercise diminish, which 
is consistent with the centrally mediated, reduced sympathetic and enhanced para- 
sympathetic activity in animals. These studies were reviewed by Jones (14), who cau- 
tioned that although marijuana's cardiovascular effects do not seem to cause serious 
health problems for young, healthy users, marijuana smoking by older people with 
cardiovascular disease poses greater risks because of the resulting increased cardiac 
work, increased catecholamines, carboxyhemoglobin, and hypotension. On the basis 
of results from a NIDA-funded study in which more than 65,000 medical charts of 
enrollees in the Kaiser Permanente Hospital system were reviewed for medical conse- 
quences of marijuana use, Sidney (15) reported no clear temporal association of mari- 
juana use with hospitalizations from cardiovascular disease. On the other hand, 
marijuana use was associated with an increased number of hospitalizations for respi- 
ratory and pulmonary complications, injuries, and slightly increased mortality (dis- 
cussed in the next paragraph). 

Regarding the pulmonary /respiratory consequences, chronic heavy smoking of 
marijuana is associated with increased symptoms of chronic bronchitis, coughing, pro- 
duction of sputum, and wheezing (16,17) and with impairment of pulmonary function, 
pulmonary responsiveness, and bronchial cell characteristics in marijuana-only smok- 
ers. Tashkin and co-workers (17) further show that chronic marijuana smoking is 
associated with poorer lung function and greater abnormalities in the large airways of 
marijuana smokers than in nonsmokers. In 1997, Tashkin and colleagues (18) reported 
that the rate of decline in respiratory function over 8 years among marijuana smokers 
did not differ from that in nonsmokers of any substance — marijuana or tobacco. How- 
ever, in another cohort there was a greater rate of decline in respiratory function among 
marijuana-only smokers than in tobacco-only smokers (19). Both studies showed that 
long-term smoking of marijuana increased bronchitis symptoms. Starr and Renneker 
(20) also reported that marijuana smokers show significantly higher levels of cyto- 
logical components in the sputum when compared with sputum from tobacco smok- 
ers. According to Tashkin and colleagues (21), marijuana smoking may predispose 



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individuals to pulmonary infection, especially patients whose immune defenses are 
already compromised by HIV infection and/or cancer and related chemotherapy. They 
report that THC produces a concentration-dependent reduction in T-cell proliferation 
and interferon-y production via a CB 2 receptor-dependent pathway. At the level of 
gene expression, THC increased expression of Thl cytokines (interferon- y/interleukin 
[IL]-2) and reduced expression of Th2 cytokines (IL-4/IL-5). Tashkin and colleagues 
(20) caution that suppression of cell-mediated immunity by THC may place marijuana 
smokers at risk for infection or cancer. Caiaff a and colleagues (22) reported that the 
incidence of bacterial pneumonia was almost four times higher in HIV-seropositive 
subjects than among HIV-negative subjects; smoking illicit drugs (marijuana, cocaine, 
or crack) had the strongest effect on risk of bacterial pneumonia among HIV-seroposi- 
tive intravenous drug users with a previous history of Peumocystic carinii pneumonia. 
On the other hand, results from a NIDA-funded, randomized, prospective, controlled 
clinical trial, in which HIV-infected patients on antiretroviral therapy smoked one 
marijuana cigarette (containing 3.9% THC) three times daily for 21 days, Brendt and 
colleagues (23) showed no significant changes in naive/memory cells, activated lym- 
phocytes, B-cells, or natural killer cell numbers that could be directly attributed to the 
administration of cannabinoids. Thus, there were no untoward effects of cannabinoids 
on immune system function in HIV patients in this short trial (23). 

Polen et al. (24) identified marijuana use as a risk factor for ill health. They 
examined the health effects of smoking marijuana by comparing the medical experi- 
ence of daily marijuana smokers who never smoked tobacco (n = 452) with a demo- 
graphically similar group of nonsmokers of either substance (n = 450). Frequent smokers 
had a small but significant increased risk of outpatient visits for respiratory illness 
(relative risk = 1.19; 95% confidence interval = 1.01, 1.41), injuries (relative risk = 
1.32; confidence interval = 1.10, 1.57), and other types of illnesses compared with 
nonsmokers. The authors concluded that daily marijuana smoking was associated with 
an elevated risk of health care use for various health problems. There was an increased 
rate of presentation for respiratory conditions among marijuana-only users, although 
its significance remains uncertain because infectious and noninfectious respiratory 
conditions were aggregated. Nevertheless, marijuana use was associated with increased 
respiratory/pulmonary complications and increased rates of hospitalizations for such 
complications among chronic marijuana smokers (12,24). 

Marijuana smoking produces histopathological changes that precede lung can- 
cer, and long-term marijuana smoking may increase the risk of respiratory cancer (25). 
Johnson and colleagues (26) presented case histories of four men with multiple, large, 
upper-zone lung bullae but otherwise relatively preserved lung parenchyma. Each had 
a history of significant exposure to marijuana. In three of the four cases, the tobacco 
smoking had been relatively small, suggesting a possible causal role for marijuana in 
the pathogenesis of this unusual pattern of bullous emphysema. aWengen (27) reported 
a case series of 34 young patients (between 20 and 40 years of age) with squamous 
cell carcinomas of the oral cavity in association with chronic smoking of marijuana 
(unfortunately the abstract reviewed did not provide the length of marijuana or other 
drug use). In another report, Caplan and Brigham (28) reported on two cases of squa- 
mous cell carcinoma of the tongue in men who chronically smoked marijuana but had 



Medical and Health Consequences of Marijuana 



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no other risk factors such as smoking of tobacco or chronic use of alcohol. Caplan (29) 
also reviewed 13 reports of cancer of the mouth and larynx among chronic marijuana 
smokers in Australia and the United States in the last 5 years. Five of the cases had no 
other risk factors, and all were young. Caplan hypothesized that deep inhalation leads 
to earlier deposition of particulate matter as a result of turbulence and internal impac- 
tion. These reports of cancers in young individuals are of concern because such can- 
cers are rare among adults under the age of 60, even those who smoke tobacco and 
drink alcohol (30), and also because smoke from each marijuana cigarette contains 
more carcinogenic chemical constituents, such as benzopyrene, than smoke from a 
tobacco cigarette (31). Thus, although no epidemiological studies show a causal rela- 
tion between lung disease, including cancer, and marijuana use, the available evi- 
dence suggests that marijuana use may increase the risk of cancer and significant adverse 
respiratory /pulmonary consequences. 

4. Hepatic and Renal Consequences 

No significant reports of hepatic effects in humans have been reported that could 
be attributed to the use of marijuana. In the case of renal effects; a few case reports 
show that use of marijuana could cause reversible renal consequences such as im- 
paired renal function (32), acute renal infarction (33), or renal insufficiency (34). 

5. Endocrine Effects 

Marijuana use affects endocrine and reproductive functions as well, inhibits the 
secretion of gonadotropins from the pituitary gland, and may act directly on the ovary 
or testis. Although the effects are subtle, it is important to determine the true incidence 
of hypothalamic dysfunction, metabolic abnormalities, and mechanism of action of 
marijuana from well-designed studies (35). Cannabinoids affect multiple reproduc- 
tive functions, from hormone secretion to birth of offspring (36). Schuel and colleagues 
reported that endocannabinoid anandamide signaling regulates sperm functions required 
for fertilization in the human reproductive tract and that abuse of marijuana could 
affect these processes (36). Chronic administration of high doses of THC lowers test- 
osterone secretions; impairs semen production, motility, and viability; and disrupts 
the ovulatory cycle in animals (37). Furthermore, according to Harclerode (38), THC 
lowers testosterone levels by lowering luteinizing hormone and follicle-stimulating 
hormone. Marijuana depresses the levels of prolactin, thyroid function, and growth 
hormone while elevating adrenal cortical steroids. Chronic exposure of laboratory 
animals (rats, mice, and monkeys) to marijuana altered the function of several acces- 
sory reproductive organs. Reduced testosterone levels leads to reduced testicular func- 
tion and reduced prostate and seminal vesicle weights. Chronic administration of 
marijuana also produces testicular degeneration and necrosis in dogs (39). 

In 1986, Mendelson and colleagues (40) reported that marijuana smoking sup- 
pressed luteinizing hormone levels in normal women but not in menopausal women 
(41 ). Barnett et al. (42) showed that testosterone levels were depressed both after smok- 
ing one marijuana cigarette and after intravenous infusion of THC. This antiandrogenic 
effect of marijuana appears to occur through action on the hypothalamic-pituitary- 



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gonadal axis (37) or, in part, from inhibition of androgen action at the receptor level 
(43). Besides a single case of retarded growth in a 16-year-old marijuana smoker (44), 
no epidemiological studies or reports show that marijuana impairs sexual maturation 
and reproduction in humans. 

6. Birth and Later Developmental Outcomes 

Marijuana administration at high doses can produce teratogenic effects in mice, 
rats, rabbit, and hamsters. In humans, although far from definitive, evidence from 
longitudinal studies with women who abused marijuana during pregnancy suggests 
that prenatal exposure to marijuana is related to some aspects of postnatal develop- 
mental deficits in the offspring (45). 

Two major studies, both funded by NIDA, have followed women who smoked 
marijuana during pregnancy to examine the developmental consequences of marijuana 
use on the offspring. The study by Fried and colleagues at the University of Ottawa, 
Canada (46,47), examined the developmental consequences of marijuana in a cohort 
of Canadian, mostly Caucasian women. Another study by Day and colleagues (48), at 
the University of Pittsburgh, examined the consequences of prenatal marijuana in mainly 
poor African American women who smoked marijuana during pregnancy. Such use 
was reported to be associated with fetal growth retardation, as shown by reduction in 
birthweight, reduced length at birth, and reduced gestation period; the latter may be a 
result of the hormonal effects of marijuana. Fried (46,47) found that in the newborns, 
marijuana use by the mother was associated with mild withdrawal symptoms and some 
autonomic disruption of nervous system state regulation. Between 6 months and 3 
years of age, after controlling for confounders, no behavioral consequences of prena- 
tal marijuana exposure were observed among the children. At 4 years of age, no dif- 
ferences were observed between exposed and nonexposed children on global tests of 
intelligence, but differences were observed in verbal ability and memory. Impairment 
of verbal ability, memory, and sustained attention were also seen at 5 and 6 years of 
age. The pattern of results suggested an association of prenatal marijuana exposure 
with impaired "executive functioning" — the latter thought to be a marker of prefrontal 
lobe functioning that may not be apparent until 4 years of age. 

Day and co-workers (48) reported similar findings of impaired cognition in chil- 
dren who were exposed prenatally to marijuana. Recently, Goldschmidt and colleagues 
(49) reported significant effects on academic achievement in 10-year-old children who 
had been exposed to prenatal marijuana. However, it is important to note that the 
cognitive effects of prenatal exposure to marijuana on the offspring are quite com- 
plex, in that marijuana exposure appears to be associated with impairment of particu- 
lar aspects of intelligence, such as tasks that require visual analysis, visual memory, 
analysis, and integration among children 9-12 as well as 13-16 years of age (50). By 
comparison, prenatal exposure to tobacco affects the overall IQ and verbal function- 
ing aspects of cognitive performance. By using the newer imaging techniques, Smith 
et al. (51) reported that, with increased exposure to prenatal marijuana, there was a 
significant increase in neural activity in bilateral prefrontal cortex and right premotor 
cortex during response inhibition. There was also an attenuation of activity in the left 



Medical and Health Consequences of Marijuana 



243 



cerebellum with increased prenatal exposure to marijuana when challenging the 
response inhibition neural circuitry. Prenatally exposed offspring had significantly 
more commission errors than nonexposed participants, but all participants were able 
to perform the task with more than 85% accuracy. These findings suggest that prenatal 
marijuana exposure is related to changes in neural activity during response inhibition 
that may last into young adulthood (51). 

7. Effects on the Brain: 
Cognitive, Psychological, and Mental Consequences 

Research by Pope and Yurgelum-Todd (52), Kouri et al. (53), Solowij et al. (54), 
and Block and Ghoneim (55) has shown that chronic use of marijuana was associated 
with impairment of cognition, particularly affecting short-term memory and executive 
functioning in humans; and this impairment did not recover after abstaining from heavy 
use of marijuana (up to 5000 times in a lifetime) for at least 24 hours (52), 1 days (56), 
or 6 weeks (54). However, in the study of Pope and colleagues (57), the subjects did 
recover after 28 days of abstinence from marijuana use. In studies by Pope and col- 
leagues (52,56,57), the subjects smoked marijuana up to 5000 times in their lifetime 
(8-15 years), whereas in the study by Solowij et al. ( 54 ), the subject had smoked approx 
6 g of marijuana each day for about 17 years. Many other older studies have also 
reported that marijuana use is associated with impairment of short-term memory and 
not "old" memory. 

Pope and Yurgelum-Todd (52) found that heavy use of marijuana is associated 
with cognitive impairment in college undergraduate students. The researchers enrolled 
two groups of students — 65 "heavy users" (38 male, 27 female), who had smoked 
marijuana a median of 29 days in the past 30 days (range 22-30) and who also dis- 
played cannabinoids in their urine, and 64 "light users" (31 male, 33 female), who had 
smoked a median of 1 day in the previous 30 days (range 0-9) and who displayed no 
urinary cannabinoids. All of the subjects were assessed by several neuropsychological 
tests when they were abstinent from marijuana and other drug use for at least 19 hours. 
The outcome measures were general intellectual functioning, abstraction ability, sus- 
tained attention, verbal fluency, and ability to learn and recall new verbal and 
visuospatial information. Heavy users displayed significantly greater impairment than 
light users in attention/executive functions, as evidenced by greater perseverations on 
card sorting and reduced learning of word lists. These differences remained after con- 
trolling for potential confounding variables, such as estimated levels of premorbid 
cognitive functioning, and for use of alcohol and other substances in the two groups. It 
is not clear whether this cognitive impairment is a reslut of a residue of drug in the 
brain, a withdrawal effect from the drug, or a frank neurotoxic effect of the drug. 

Similarly, Fletcher and colleagues (58) reported cognitive impairment from 
chronic marijuana use, but in older subjects. They studied two cohorts of older chronic 
cannabis-using and cannabis-nonusing adult men. Both cohorts were comparable in 
age and socioeconomic status. Polydrug users and users who tested positive for use of 
cannabis at the time of cognitive assessment after a 72-hour abstention period were 
excluded. The older cohort (17 users, 30 nonusers; mean age 45 years) had consumed 



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cannabis for an average of 34 years; the younger cohort (37 users and 49 nonusers; 
mean age 28 years) had consumed cannabis for an average of 8 years. Each subject 
received measures of short-term memory, working memory, and attentional skills. 
Results showed that the older chronic users performed more poorly than older nonus- 
ers on two short-term memory tests involving lists of words and on selective and 
divided attention tasks associated with working memory. No significant differences 
were apparent between younger users and nonusers. The authors concluded that long- 
term cannabis use was associated with disruption of short-term memory, working 
memory, and attention skills in older long-term cannabis users. 

Crowley and colleagues (59) examined 89 seriously delinquent, drug-dependent 
adolescent males 2 years after their admission to a residential treatment program. All 
had at least three lifetime symptoms of conduct disorder. Of these boys, 82% were 
dependent on alcohol and 81% were dependent on cannabis, and many also were 
dependent on a wide variety of other substances. The boys were very aggressive by 
history, and more than half had committed a crime in the past month. Many of them 
also had major depression and/or attention deficit hyperactivity disorder (ADHD) at 
the time of admission. Nearly half had been in jail or detention just before admission. 
When followed up 2 years later, the boys showed highly significant reduction in anti- 
social and criminal acts. Both major depression and ADHD had nearly disappeared. 
About 40% of the group had achieved high school graduation or GED equivalency at 
the time of follow-up. However, the number reporting recent drug use had changed 
little, although the prevalence of heavy daily use had significantly declined. Research 
shows that seriously delinquent adolescents who are heavily involved in drug-taking 
behavior can improve in antisocial behaviors and depression after treatment. But the 
authors emphasize the need for more research on effective treatments for the drug 
dependence commonly found among delinquents. 

Crowley and colleagues (60) carried out a study to determine the consequences 
of marijuana use among adolescents. The subjects were 165 male and 64 female 13- to 
19-year-old patients recruited from a university treatment program for delinquent, 
substance-involved youths who had been referred for substance use and conduct prob- 
lems (usually from social service or criminal justice agencies). The admission criteria 
were one or more dependence diagnoses and three or more lifetime conduct disorder 
symptoms (stealing, lying, running away, physical cruelty). The diagnoses were: sub- 
stance dependence, 100%; conduct disorder, 82%; major depression, 17.5%; and 
ADHD, 14.8%. Standardized diagnostic interview instruments were used for substance 
dependence, psychiatric disorders, and patterns of substance abuse. Results showed 
that of the 229 teens, 220 had dependence on at least one nontobacco substance and 9 
were dependent on tobacco with abuse of other substances. On average the youths 
were dependent on 3.2 substances, with marijuana and alcohol producing the most 
cases. Among the marijuana-dependent teens, 31.2% reported at least daily use of 
marijuana in the previous year. The rate of progression from first to regular marijuana 
use was as rapid as tobacco progression and more rapid than that of alcohol, indicating 
potent reinforcing effects of marijuana. Most patients described serious problems from 
marijuana: more than 80% of male and 60% of female patients met criteria for mari- 
juana dependence, 66% of marijuana-dependent patients reported withdrawal, and more 



Medical and Health Consequences of Marijuana 



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than 25% had used marijuana to relieve withdrawal symptoms (e.g., irritability, rest- 
lessness, insomnia, anorexia, nausea, sweating, salivation, elevated body temperature, 
tremor, and weight loss) that were clinically significant. About 85% said that mari- 
juana interfered with their responsibilities at school, at work, or at home or endan- 
gered them while, for example, driving. Finally, the patients reported that in most 
cases, conduct problems arose before marijuana use, which typically began around 
the time of appearance of the third conduct disorder symptom. In summary, among 
adolescents with conduct problems, marijuana is not benign; moreover, its use by 
susceptible youths may be considered unsafe. It was stated that marijuana potentially 
reinforced marijuana taking, producing both dependence and withdrawal (59,60). 

Although "cannabis psychotic disorder" with delusions or with hallucinations is 
recognized in the Diagnostic and Statistical Manual of Mental Disorders, 4th ed., 
relatively little information is available on this disorder. Gruber and Pope (61) re- 
viewed 395 eligible charts of the 9432 admissions at two psychiatric centers between 
April 1991 and October 1992 and October 1989 and November 1992, respectively, 
seeking cases of cannabis-induced disorders. There were no convincing cases of a 
cannabis-induced psychotic syndrome. The authors also reviewed published studies 
on the subject. There were 10 series of 10 or more cases, all describing primarily 
cannabis-induced psychotic syndromes. None of the 10 studies was performed in the 
United States; only two have been published in the last 10 years, neither of which 
supported the existence of a distinct cannabis-induced psychosis. Furthermore, most 
studies were retrospective and uncontrolled. The overall evidence from both reviews 
was insufficient to prove that marijuana alone can produce a psychotic syndrome in 
previously asymptomatic individuals, and further research is needed to validate the 
diagnosis of cannabis psychosis (61). On the other hand, more recent and excellent 
reviews by Zammit and colleagues (62), Aresneault et al. (63), and Smit et al. (64) 
show that marijuana use is causally associated with the development of psychosis. For 
example, Zammit and colleagues concluded that cannabis use is associated with an 
increased risk of developing schizophrenia, consistent with a causal relation, and that 
this association is not explained by the use of other psychoactive drugs or personality 
traits relating to social integration. Aresneault et al. (63) also stated that on an indi- 
vidual level, cannabis use increases the risk at least twofold in the relative risk for 
later schizophrenia, while at the population level, elimination of cannabis would re- 
duce the incidence of schizophrenia by approx 8% assuming a causal relationship. 
Similarly, Smit and colleagues (64) also suggested a relationship between cannabis 
use and schizophrenia. The reader is further directed to these excellent reviews on 
marijuana and psychosis. 

8. Marijuana Dependence 

Animal and human studies show that marijuana can produce tolerance and 
dependence. Lichtman and Martin (65) have shown that abstinence leads to clinically 
significant withdrawal symptoms that can be precipitated by treating the marijuana- 
dependent animals with a cannabinoid receptor antagonist, SR14176A. The most promi- 
nent signs of marijuana withdrawal in rats were wet-dog shakes; less frequent signs 



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included grooming, retropulsion, and stretching; while the most prominent signs in 
the mice were head shakes and paw tremors. Similarly, mice exposed repetitively to 
marijuana smoke exhibit a dependence syndrome similar to that produced by THC. 
The development of cannabinoid or marijuana dependence in laboratory animals was 
consistent with marijuana dependence in humans (57,66). Moreover, marijuana de- 
pendence is much more similar than dissimilar to other forms of drug dependence 
(67). In humans, daily marijuana smoking in healthy individuals produces dependence, 
as demonstrated by withdrawal symptoms such as increased irritability and anxiety 
and decreased food intake. Furthermore, some aspects of marijuana dependence can 
be treated. During marijuana abstinence, sustained-release bupropion increases rat- 
ings of irritability, depression, and stomach pain and decreases food intake compared 
with placebo, suggesting ineffectiveness, whereas nefazodone was effective in 
decreasing anxiety during marijuana withdrawal compared with placebo. Nefazodone 
also did not alter the ratings of irritability and misery during withdrawal (66-68). 

Withdrawal of marijuana after chronic use leads to "inner unrest," increased 
activity, irritability, insomnia, and restlessness in humans (69). Common symptoms 
reported were hot flashes, sweating, rhinorrhea, loose stools, hiccups, and anorexia. 
These symptoms were reduced by resumption of marijuana use (70). Studies from 
Sweden have shown that chronic marijuana users seeking treatment became depen- 
dent on marijuana and were unable to give up its use (71). Further epidemiological 
evidence (72,73) also supports the observation that chronic marijuana use produces 
dependence, the consequences of which are the loss of control over their drug use, 
cognitive and motivational impairments that interfere with occupational performance, 
lowered self-esteem and depression, and the complaints of spouses and partners. 

In terms of marijuana- associated amotivational syndrome, the available evidence 
is equivocal. Research is needed to study this rare, inadequately defined, and insuffi- 
ciently studied clinical consequence of prolonged heavy marijuana use. 

9. Genetic Effects 

Research shows a more than threefold and more than twofold increase over non- 
smoking pregnant women in mutations of the hypoxanthine phosphoribosyl transferase 
(hprt) gene in among pregnant women who smoked marijuana and cigarettes, respec- 
tively, early in their pregnancies and before (74). Authors indicated that these obser- 
vations from a preliminary study suggest that marijuana smokers may have an elevated 
risk of cancer. For pregnant marijuana smokers, there is also concern about the possi- 
bility of genotoxic effects on the fetus, resulting in heightened risk of birth defects or 
childhood cancer. 

The role of genetics in marijuana abuse was suggested by the studies of Tsuang 
and colleagues (75-77). In a twin study of drug abuse, 4000 pairs of twins — monozy- 
gotic and dizygotic — were assessed for drug abuse and dependence. They showed that 
marijuana use was affected to a great extent by genetic factors. The common or family 
environment made a significant contribution to the use of marijuana. Initiation of 
marijuana use could be influenced by characteristics of the environment (drug avail- 
ability, peer groups) and the characteristics of the individual (personality). For the 
continuation of drug use, other individual characteristics, such as physiological and 



Medical and Health Consequences of Marijuana 



247 



subjective reactions to the drugs, may be important. Furthermore, among the mari- 
juana users, suspiciousness and agitation appeared to be genetically related, whereas 
the pleasant psychological effects appeared to be mediated by the twins' shared envi- 
ronment, and not by genes. Using this twin model, additional studies are underway to 
examine the medical and health consequences, including psychiatric consequences, of 
drug abuse and genetic influences on drug use/abuse and associated conduct disorders 
and antisocial behaviors in childhood and later in adults. 

10. Marijuana and Health 

Sidney (15) and Polen et al. (24) at Kaiser Permanente HMO reviewed the medi- 
cal charts of approx 65,000 patients and showed that, after adjusting for gender, age, 
race, education, marital status, and alcohol use, frequent marijuana smokers (duration 
of marijuana use between 5 and 15 years) had an increased risk of making outpatient 
visits for respiratory illness, injuries, and "other" illnesses compared with nonsmokers. In 
addition, the relative risk of cervical cancer among women who used marijuana but never 
smoked tobacco was 1 .42 compared with those who used marijuana. However, there was 
no increased risk for other cancers in association with marijuana use. There was an increased 
risk of mortality associated with ever using marijuana among men, AIDS (probably reflec- 
tive of lifestyles), injury/poisoning, and other causes of death, whereas among marijuana 
using women, there was a decreased risk for mortality. 

11. Marijuana and Cancer 

It is currently unclear whether long-term smoking of marijuana causes cancer. 
As mentioned above, marijuana smoke contains more carcinogenic chemical constitu- 
ents than tobacco smoke (31); thus, one might expect to see more cases of lung cancer 
than with tobacco smoking. However, no significantly large number of cases of lung 
cancer or other cancers has been reported in marijuana smokers, possibly because no 
such studies have ever been conducted. Recently, after controlling for age, sex, race, 
education, alcohol consumption, pack-years of cigarette smoking, and passive smok- 
ing, Zhang and colleagues (78) reported that the risk of squamous cell carcinoma of 
the head and neck was increased with marijuana use in a strong dose-response pat- 
tern. The researchers also suggested that marijuana use might interact with mutage- 
nicity and other risk factors to increase the risk of head and neck cancer. However, the 
investigators noted that the results should be interpreted with some caution in drawing 
causal inferences because of certain methodological limitations, especially with re- 
gard to interactions between marijuana smoking and concomitant use of alcohol and 
tobacco. On the other hand, on the basis of a large case-control study of head, neck, or 
lung cancer in marijuana smokers, Hashibe et al. (79) reported that although the use of 
tobacco and alcohol was associated with these cancers, the use of marijuana was not 
associated with these cancers in young adults. 

12. Marijuana and Highway Accidents 

The published evidence suggests that marijuana use may impair motor perfor- 
mance. In a recent review, Ramaekers and colleagues (80) report that both epidemio- 



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logical and experimental studies show that marijuana use is associated with motor 
accidents. Further, they state that combined use of THC and alcohol produced severe 
impairment of cognitive, psychomotor, and actual driving performance in experimen- 
tal studies and sharply increased the crash risk in epidemiological analyses. Signifi- 
cantly increased rates of motor vehicle injuries resulting in hospitalization have also 
been reported among marijuana users (81). Despite many reports in the published 
literature, the incidence and prevalence of accidents causally related to marijuana use 
are not known. More research is needed to establish a causal association between 
marijuana use and traffic accidents. 

13. Summary 

For the past several years marijuana has been the most commonly abused drug in 
the United States, with approx 6% of the population 12 years and older having used 
the drug in the month before interview. The use of marijuana is not without significant 
health risks. Marijuana is associated with effects on almost every organ system in the 
body, ranging from the central nervous system to the cardiovascular, endocrine, respi- 
ratory/pulmonary, and immune systems. Research shows that in addition to marijuana 
abuse/dependence, marijuana use is associated with serious health consequences in 
some studies with impairment of cognitive function in the young and old, fetal and 
developmental consequences, cardiovascular effects (heart rate and blood pressure 
changes), respiratory /pulmonary complications such as chronic cough and emphy- 
sema, impairment of immune function, and risk of developing head, neck, and/or lung 
cancer. In general, acute effects are better studied than those of chronic use, and more 
studies are needed that focus on disentangling effects of marijuana from those of other 
drugs and adverse environmental conditions. More research is needed in the following 
areas: (1) the general health consequences of marijuana use, neurocognitive effects of 
chronic marijuana use by adolescents and young adults using traditional as well as 
newer imaging techniques; marijuana dependence in animal models and humans; mari- 
juana effects in various human diseases (endocrine, pulmonary /respiratory diseases; 
immune dysfunction-related infections); effects of chronic marijuana use on sleep dis- 
orders; drug interactions between marijuana and medications used in the treatment of 
mental disorders or other diseases; effects of acute and chronic marijuana use on the 
reproductive system; and functional assays to study neuropsychiatric/behavioral effects; 
(2) in the cardiovascular area, the effects of chronic marijuana use and atherosclerotic 
events (effects on clotting mechanisms; lipid metabolism) and endothelial function; 
arrhythmic effects of chronic marijuana use; effects on body weight resulting from 
plasma fluid retention (renal effects via renin-angiotensin-aldosterone system); and 
long-term effects on coronary output using noninvasive techniques; (3) future pulmo- 
nary and cancer studies addressing lung immunity among chronic marijuana smokers; 
incidence, prevalence, and underlying pathophysiology (molecular/genetic basis) of 
head and neck cancer and other cancers (cervix, prostate) associated with chronic 
marijuana use; population epidemiological studies; and tumor registries to determine 
whether chronic marijuana smoking is associated with cancers; and finally (4) train- 
ing for new investigators and those from other disciplines to conduct research on the 
medical and health consequences of marijuana. 



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19. Sherrill, D. L., Kryzanowski, M., Bloom, J. W., and Lebowitz, M. D. (1991) Respiratory 
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26. Johnson, M. K., Smith, R. P., Morrison, D., Laszlo, G., and White, R. J. (2000) Large lung 
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27. aWengen, D. F. (1993) Marijuana and malignant tumors of the upper aerodigestive tract in 
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33. Lambrecht, G. L., Malbrain, M. L., Coremans, P., Verbist, L., and Verhaegen, H. (1995) 
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35. Brown, T. T. and Dobs, A. S. (2002) Endocrine effects of marijuana. /. Clin. Pharmacol. 
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36. Schuel, H., Burkman, L. J., Lippes, J., et al. (2002) Evidence that anandamide- signaling 
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37. Bloch, E. (1983) Effects of marijuana and cannabinoids on reproduction, endocrine func- 
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38. Harclerode, J. (1984) Endocrine effects of marijuana in the male: preclinical studies. NIDA 
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39. Dixit, V. P., Gupta, C. L., and Agarwal, M. (1977) Testicular degeneration and necrosis 
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40. Mendelson, J. H., Mello, K., Ellingboe, J., Skupny, A. S., Lex, B. W., and Griffin, M. 
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41. Mendelson, J. H., Cristofaro, P., Ellingboe, J., Benedikt, R., and Mello, N. K. (1985) Acute 
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42. Barnett, G., Chiang, C. W., and Licko, V. (1983) Effects of marijuana on testosterone in 
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43. Purohit, V., Ahluwalia, B. S., and Vigersky, R. A. (1980) Marihuana inhibits 
dihydrotestosterone binding to the androgen receptor. Endocrinology 107(3), 848-850. 

44. Copeland, K. C, Underwood, L. E., and Van Wyck, J. J. (1980) Marijuana smoking and 
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45. Khalsa, J. H. and Gfroerer, J. (1991) Epidemiology and health consequences of drug abuse 
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46. Fried, P. A. (1995) The Ottawa prenatal prospective study (OPPS): methodological issues 
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47. Fried, P. A. (1995) Prenatal exposure to marihuana and tobacco during infancy, early and 
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48. Day, N. L., Richardson, G. A., Goldschmidt, L., et al. (1994) Effect of prenatal marijuana 
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49. Goldschmidt, L., Richardson, G. A., Cornelius, M. D., and Day, N. L. (2004) Prenatal 
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50. Fried, P. A., Watkinson, B., and Gray, R. (2003) Differential effects on cognitive function- 
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51. Smith, A. M., Fried, P. A., Hogan, M. J., and Cameron, I. (2004) Effects of prenatal mari- 
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52. Pope, H. G., Jr, Gruber, A. J., and Yurgelum-Todd, D. (1995) The residual neuropsycho- 
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230-237. 



Chapter 11 



Effects of Marijuana on the Lung 
and Immune Defenses 

Donald P. Tashkin and Michael D. Roth 

1. Introduction 

Cannabis has been used as a drug for thousands of years, but marijuana smoking 
has become prevalent in Western society only during the last 40 years ( 1,2). An annual 
survey conducted in the United States from 1975 to 2002 documented that marijuana 
is now the second most commonly smoked substance after tobacco (1,2). Marijuana 
smoke, like tobacco smoke, is generated by the pyrolysis of dried plant leaves. As a 
result, it shares thousands of chemical features in common with tobacco smoke, 
including qualitatively similar amounts of carbon monoxide, cyanide, acrolein, ben- 
zene, vinyl chlorides, aldehydes, phenols, nitrosamines, reactive oxygen species (ROS), 
and a variety of polycyclic aromatic hydrocarbons (3,4). The primary distinction 
between marijuana and tobacco is the presence of A 9 -tetrahydrocannabinol (THC) and 
other cannabinoids in Cannabis vs the presence of nicotine in tobacco (3,4). Although 
the hazardous effects of tobacco smoking have been extensively documented and 
include emphysema, chronic obstructive pulmonary disease (COPD), heart disease, 
and risk for developing several different types of cancer, studies on the health effects 
of marijuana smoking are less abundant. The common perception is that marijuana 
smoke is less toxic and that smoking a few marijuana joints per day has far fewer 
consequences than smoking a pack of tobacco cigarettes (5). However, the lack of 
filtering and differences in the smoking technique associated with marijuana use result 
in an approximately fourfold greater deposition of tar particulates in the lung than 
occurs from smoking similar amounts of tobacco (6). In addition, the concentration of 
pro-carcinogens such as benz- [a] -anthracene and benzo-[a]-pyrene are up to twofold 
higher in marijuana tar (3,7). The presence of irritants and pro-carcinogens in mari- 

From: Forensic Science and Medicine: Marijuana and the Cannabinoids 
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey 

253 



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EFFECTS OF MARIJUANA ON THE 
LUNG AND HOST DEFENSES 



LUNG 



■ Increase cough and sputum 

■ Impair pulmonary function 

1 Produce airway inflammation 
• Epithelial injury / dysplasia 

■ Precancerous changes 




CELL FUNCTION 



1 Reactive oxygen injury 
1 Regulation of apoptosis 
1 Cytochrome P4501A1 
• Disrupt mitochondrial 
function & cell energetics 



IMMUNE DEFENSES 



• Activation of CB1 and CB2 

' Impair alveolar macrophages 

• Regulate Th1/Th2 cytokines 

• Suppress host responses to 
infection and cancer 



Fig. 1 . Habitual marijuana smoking delivers toxic smoke components and high 
concentrations of tetrahydrocannabinol to the lung with subsequent effects on the 
lung, respiratory cell function, and host immune defenses. 



juana smoke and the enhanced deposition of these in the lung during smoking suggest 
that habitual smoking of marijuana might result in a spectrum of respiratory conse- 
quences similar to those described for tobacco smoking. Moreover, THC has recently 
been shown to exert potent biological effects on lung epithelial cells and on the immune 
system (8-10). Consequently, it is possible that regular exposure to marijuana smoke, 
a large proportion of which is THC, might predispose to lung injury, pulmonary infec- 
tions, and/or tumor growth. This chapter reviews the current knowledge concerning 
the pulmonary and immune consequences of marijuana smoking and THC, as briefly 
outlined in Fig. 1 . 

2. Acute Effects of Marijuana on Airway Physiology 

Although anecdotal reports dating back to the 19th century suggested a thera- 
peutic role for marijuana in the relief of asthma, formal experiments first documented 
this effect in the 1970s. Smoke from marijuana cigarettes was found to produce short- 
term bronchodilation both in healthy individuals (11,12) and in patients with asthma 
( 13). This bronchodilator effect was clearly attributable to the presence of THC, because 
oral administration of synthetic THC also produced a dose-dependent bronchodilatation 
(11). Recently, a potential mechanism for this effect on bronchomotor tone was iden- 
tified. Cannabinoid type 1 (CB,) receptors were found on axon terminals of postgan- 
glionic parasympathetic nerve fibers in rat lung. These nerve terminals are in close 
proximity to airway smooth muscle (14). In the guinea pig airway, stimulation of 
these receptors by the endogenous cannabinoid anandamide resulted in dose-depen- 
dent relaxation of capsaicin-contracted airway smooth muscle, whereas anandamide 
caused dose-dependent bronchoconstriction in vagotomized preparations in which air- 
way smooth muscle was maximally relaxed (14). These observations suggest that the 



Effects of Marijuana on Immune Defenses 



255 



endogenous cannabinoid system may play a regulatory role in the bidirectional con- 
trol of airway smooth muscle tone. 

From a clinical standpoint, however, smoking marijuana does not have a thera- 
peutic role in obstructive airways diseases such as asthma. Despite its short-term bron- 
chodilator properties, the long-term pulmonary consequences of marijuana smoking 
include airway inflammation, edema, and mucus hypersecretion (5). On the other hand, 
the development of aerosolized preparations of pure THC for inhalation (15) could 
produce local physiological effects with a rapid and reproducible onset of action. How- 
ever, inhalation of pure THC has been shown to induce bronchospasm in individuals 
with airways hyperreactivity because of local irritant effects (16). THC can also dis- 
rupt mitochondrial function and the generation of adenosine triphosphate (ATP) in 
airway epithelial cells, as well as promote necrotic cell death (8,17). These toxic effects 
occur rapidly, and the impact of THC on mucociliary function and noxious lung injury 
can be significant. 

3. Effects of Habitual Marijuana Exposure on the Lung 

3.1. Animal Studies 

Several long-term animal exposure studies (dog, rat, monkey) have demonstrated 
extensive inflammatory changes in small airways (bronchioles) and focal inflamma- 
tion within the lung parenchyma, as well as proliferative alterations in alveolar epithe- 
lium ( 18-20). On the other hand, a carefully conducted study in rats in which animals 
were exposed to increasing concentrations of marijuana or tobacco smoke for 1 year 
demonstrated morphological and physiological changes of emphysema (decreased 
alveolar surface area and reduced lung elastic recoil) in the tobacco-exposed rats but 
not in the animals exposed to a similar quantity of marijuana (21 ). The results of these 
animal studies are difficult to extrapolate to humans because of differences in expo- 
sure of different regions of the respiratory system to the inhaled smoke as well as 
species differences. 

3.2. Human Studies 

3.2.1. Older Studies on the Effects of Cannabis on Respiratory 
Disorders and Lung Function 

Several older human studies conducted in the 1970s yielded conflicting results 
concerning the impact of regular cannabis use on clinical features of chronic respira- 
tory disease and/or lung function (22-25). These results are difficult to interpret because 
the studies were mostly small in scale, cross-sectional in design, and subject to selec- 
tion bias. In addition, many of them failed to control adequately for the important 
confounding effect of concomitant tobacco use. 

3.2.2. Newer Studies on the Pulmonary Consequences of Marijuana Use 

Three relatively large-scale, controlled observational studies of the pulmonary 
consequences of regular use of marijuana have been conduced since 1980. One longi- 
tudinal cohort study reported on a convenience sample of heavy habitual smokers of 
marijuana alone (MS; N = 144) or with tobacco (MTS; N = 134), regular smokers of 



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Table 1 

Pulmonary Consequences of Habitual Marijuana Use 

• Increased prevalence of acute and chronic bronchitis (26,28,30) 

• Inconsistent evidence of mild, progressive airflow obstruction (26-31) 

• Visual evidence of airway inflammation (mucosal erythema, edema, and increased secre- 
tions) that correlates with inflammatory findings on airway biopsy (5) 

• Histopathological alterations in tracheobronchial epithelium and subepithelium, including 
squamous metaplasia, basal cell hyperplasia, goblet cell hyperplasia, loss of ciliated sur- 
face epithelium, basement membrane thickening, epithelial inflammation, cellular disorga- 
nization, and increased nuclear-to-cytoplasm ratio (35,36) 

• Overexpression of epidermal growth factor receptor and Ki-67, a nuclear marker of cell 
proliferation, by bronchial epithelial cells suggesting dysregulated growth and a risk for 
progression to bronchogenic carcinoma (36) 

• Epidemiological evidence of increased risk for both bacterial and opportunistic pneumonia 
in HIV-seropositive individuals (83-85) 



tobacco alone (TS; N = 80), and nonsmokers of either substance (NS; N = 99) re- 
cruited from the greater Los Angeles area (26,27). A second cohort study reported on 
a random stratified sample of young residents of Tucson, AZ (28,29). The third study 
was a population-based approach employing a birth cohort of individuals residing in 
Dunedin, New Zealand (30,31). Results of these studies have revealed a number of 
adverse pulmonary consequences of habitual marijuana use (Table 1). 

3.2.2.1. Respiratory Symptoms 

All three studies reported comparable results with respect to the association 
between regular marijuana smoking and chronic respiratory symptoms: the prevalence 
of chronic cough and/or sputum and wheeze was significantly higher in the marijuana 
smokers than in the nonsmokers, indicating a link between regular marijuana use and 
symptoms of chronic bronchitis. In the Los Angeles study, the incidence of acute 
lower respiratory infections was also higher in both MS and TS than NS, and the 
prevalence of chronic respiratory symptoms was comparable between MS and TS 
without evidence of additive effects in those who smoked both substances (26,27). 
However, an additive adverse effect of combined marijuana and tobacco smoking was 
suggested in the Tucson study (28,29). 

3.2.2.2. Lung Function 

The Los Angeles study failed to reveal any association between marijuana smoking 
and abnormalities on pulmonary function tests including sensitive tests of small air- 
way function, the major site of involvement in COPD, and the diffusing capacity for 
carbon monoxide, a sensitive physiological indicator of emphysema. Moreover, no 
impact of even heavy regular smoking of marijuana alone (average of three joints per 
day) was found on the annual rate of change in the forced expiratory volume in 1 
second (FEV[), an indicator of obstructive lung disease. In contrast, TS from the same 
cohort study demonstrated an accelerated rate of loss of FEVj (27), consistent with the 
known predisposition of tobacco smokers to the development of COPD. These find- 
ings, therefore, did not support the concept that marijuana smoking leads to the devel- 



Effects of Marijuana on Immune Defenses 



257 



opment of COPD and are consistent with the results of the rat exposure experiments 
cited above. In contrast, both the Tucson study and the Dunedin study did find evi- 
dence of mild airflow obstruction in association with marijuana use (28,30), and the 
airflow obstruction progressed over time in the continuing marijuana users (29,31 ). In 
contrast to the Los Angeles study, these two reports suggest that regular use of mari- 
juana may be a risk factor for the subsequent development of COPD. 

A specialized test of lung function that serves as a measure of alveolar epithelial 
permeability was carried out in a subset of the participants in the Los Angeles study 
(32). This test measures the rate of clearance from the lung of a radiolabeled small 
molecule ( 99m Tc-DTPA) after inhalation. Elimination of the 99m Tc-DTPA through the 
normally tight junctions between adjacent alveolar epithelial cells is accelerated in the 
presence of epithelial cell injury. Interestingly, while the results of this test were ab- 
normal in regular tobacco smokers, consistent with tobacco-related lung injury, find- 
ings in the regular smokers of marijuana only (MS) were similar to those in nonsmoking 
healthy control subjects (NS). These negative results parallel the findings of a normal 
diffusing capacity for carbon monoxide in the MS and provide further evidence of 
disparate effects of marijuana and tobacco on lung function. 

Thus, the available evidence is mixed and contradictory with regard to the pos- 
sible link between marijuana and COPD. Clearly, further research is required to re- 
solve these conflicting findings. 

3.2.2.3. Effects on Airway Injury and Bronchial Epithelial Pathology 

A subset of MS, TS, MTS, and NS from the Los Angeles cohort underwent 
fiberoptic bronchoscopy during which videotapes of the tracheobronchial airway 
mucosa were recorded and a series of mucosal biopsies obtained. The videotapes were 
reviewed in a blinded manner for the presence and degree of airway injury according 
to a semiquantitative scoring system ("bronchitis index"; ref. 5). Visual evidence of 
airway injury among the MS comparable to that noted in the TS was identified with 
abnormal scores for mucosal erythema, swelling, and increased secretions as com- 
pared to control NS. These visual abnormalities were corroborated by histopathologi- 
cal alterations on the mucosal biopsies in which an increased number and size of 
submucosal blood vessels, submucosal edema, and hyperplasia of the mucus-secret- 
ing surface epithelial cells (goblet cells) were observed. These findings indicate that 
regular smoking of marijuana by young adults leads to the same frequency, type, and 
degree of aiway inflammation as that seen in the lungs of regular tobacco smokers, 
despite a marked difference in the number of cigarettes smoked for the two types of 
substances (~3 joints per day in the MS vs 22 tobacco cigarettes per day in the TS). 

It is possible that the presence of THC in marijuana smoke directly contributes to 
this higher than expected degree of airway injury. During smoking, THC is concen- 
trated in the particulate phase of the smoke and deposited onto the respiratory mucosa. 
To examine its potential impact on cell function, endothelial cells (ECV 304 cell line), 
lung tumor cells (A549 cell line), and primary human airway epithelial cells were 
exposed in vitro to either purified THC or to smoke from marijuana cigarettes 
(8,17,33,34). Exposure to whole marijuana smoke stimulated the formation of more 
ROS than did exposure to the same amount of tobacco smoke. Furthermore, the mag- 
nitude of ROS was directly proportional to the concentration of THC in the cigarettes 



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(33). Marijuana smoke exposure was also associated with a reduction in intracellular 
glutathione and a toxic effect on mitochondial electron transport, resulting in ATP 
depletion (8,33,34). Mitochondrial dysfunction was observed with both purified THC 
and with the tar extracts from marijuana cigarettes, but not when cells were exposed to 
extracts from placebo marijuana smoke (not containing THC) or regular tobacco smoke. 
ATP depletion may impair important energy-dependent functions, including ciliary 
activity, phagocytosis, and normal fluid and electrolyte transport. Another potential 
consequence of mitochondial toxicity is an inhibition of apoptosis and the promotion 
of necrotic cell death, a pattern observed when respiratory epithelial cells are exposed 
to THC in vitro (17,34). The shift from apoptotic to necrotic cell death has been shown 
in animal models to disrupt normal epithelial defenses and promote inflammation and 
infection. Further studies are required to determine the relevance of these toxic cellu- 
lar effects of THC to the degree of lung injury observed in marijuana smokers. 

Bronchial mucosal biopsies were also obtained during fiberoptic bronchoscopy 
from 40 MS, 31 TS, 44 MTS, and 53 NS as part of their participation in the Los 
Angeles study (35). Light microscopy revealed extensive histopathological abnormali- 
ties in the epithelium of the MS, including goblet cell hyperplasia, reserve cell hyper- 
plasia, squamous metaplasia, cellular disorganization, nuclear atypia, increased mitotic 
index, increased nuclear/cytoplasmic ratio, and inflammatory changes. These abnor- 
malities were comparable to those noted in the TS, and the data suggested additive 
changes resulting from habitual use of both substances in the MTS. Some of these 
histological alterations are associated with the subsequent development of bronchogenic 
carcinoma in tobacco smokers (36). 

Immunohistology was used to examine bronchial biopsies from 52 of the previ- 
ously mentioned subjects for abnormal expression of genes involved in the pathogen- 
esis of lung cancer, including overexpression of epidermal growth factor receptor (Fig. 
2), a pathway that promotes autonomous cell growth, and Ki-67, a nuclear prolifera- 
tion protein involved in cell replication (36). Results of these immunohistochemical 
studies revealed marked overexpression of epidermal growth factor receptor and Ki- 
67 among the MS compared to the NS and even numerically greater expression than 
was noted in the TS, with the suggestion of additivity in the MTS. Together with the 
aforementioned light microscopic changes, these findings suggest that regular mari- 
juana smoking damages the airway epithelium, leading to dysregulation of bronchial 
epithelial cell growth and potentially malignant transformation. 

3.2.2.4. Effects on Alveolar Macrophages 

Alveolar macrophages (AM) are key immune effector cells in the lung that pro- 
tect against infection and other noxious insults. AM were recovered by bronchoalveolar 
lavage during the bronchoscopy studies performed on subjects studied in Los Ange- 
les. The number of AM recovered from MS was approximately twice that from NS, 
whereas the yield of AM from TS and MTS was three and four times that of NS, 
respectively, indicating an additive effect of the two substances on either AM recruit- 
ment to, and/or replication in, the lung (Table 2; Fig. 3; refs. 37 and 38). The increased 
accumulation of AM in the lungs of MS may be viewed as an inflammatory response 
to chronic low-grade lung injury from habitual exposure to irritants, including 
oxyradicals, within the smoke of marijuana. Ultrastructural examination of AM 



Effects of Marijuana on Immune Defenses 259 




Fig. 2. Habitual marijuana smoking is associated with abnormal expression of epider- 
mal growth factor receptor (EGFR), a growth factor receptor that promotes autonomous 
cell growth. Airway mucosal biopsies were obtained from a cohort of nonsmokers and 
smokers of marijuana alone, tobacco alone, or both marijuana and tobacco, and 
evaluated for EGFR expression by immunohistology. Compared to the limited basal 
staining present in normal epithelium (left panel), biopsies demonstrated diffuse and 
dark staining of epithelial cells in 58% of marijuana smokers (right panel) and in 89% 
of those who smoked both marijuana and tobacco (not shown). 



Table 2 

Effects of Marijuana on Human Alveolar Macrophages 

• Increased number of alveolar macrophages recovered by bronchoalveolar lavage from 
habitual marijuana smokers compared to nonsmokers (37,38) 

• Increased size of intracytoplasmic inclusions (39) 

• Impaired ability to kill Candida albicans (40) and Candida pseudotropicalis (41) 

• Impaired phagocytosis and killing of Staphylococcus aureus (41,42) 

• Decreased respiratory burst activity (superoxide anion production) under both basal and 
stimulated conditions (40) 

• Limited tumoricidal activity against tumor cell targets in vitro (41) 

• Reduced production of proinflammatory cytokines (tumor necrosis factor-a, interleukin-6, 
and granulocyte macrophage-colony-stimulating factor [GM-CSF]) when stimulated by 
bacterial lipopolysaccharide (41) 

• Inability to express inducible nitric acid synthase or produce nitric oxide upon exposure to 
pathogenic bacteria, largely reversed by stimulation with proinflammatory cytokines such 
as GM-CSF and interferon-y (42) 



recovered from MS revealed large irregular-shaped cytoplasmic inclusions that most 
likely contain particulates from marijuana tar, possibly including metabolites of THC 
and other cannabinoids (39). AM from TS also show abnormal cytosolic inclusion 
bodies, and the number of these inclusions is dramatically increased in smokers of 
both marijuana and tobacco (39). It seems plausible that the presence of a large num- 
ber of abnormal inclusion bodies within the cytoplasm of AM from smokers of mari- 
juana and/or tobacco might interfere with the function of these important immune 
effector cells. 



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Smoking Groups 

Fig. 3. The number of alveolar macrophages (AM) increases in response to smoking. 
Bronchoalveolar lavage was used to recover AM from the lungs of nonsmokers (NS) 
and smokers of marijuana alone (MS), tobacco alone (TS), or both marijuana and 
tobacco (MTS). The number of AM recovered from MS was approximately twice that 
from NS, while the yield of AM from TS and MTS was three and four times that of NS, 
respectively, indicating an additive effect of the two substances on the recruitment 
and/or replication of macrophages in the lung. 



The function of AM recovered from a subset of MS, TS, MTS, and NS was 
systematically evaluated ex vivo with respect to their phagocytic and killing activity 
for fungi and bacteria, their production of reactive oxygen and nitrogen intermediates 
during incubation with fungal or bacterial microorganisms, their ability to produce 
pro-inflammatory cytokines when stimulated, and their cytotoxic activity against tu- 
mor cell targets. Briefly, findings from these studies showed the following: (1) an 
impairment in fungicidal activity against Candida albicans and Candida tropicalis 
when AM from both MS and TS were compared to AM collected from control NS 
(40,41); (2) impairment in phagocytosis and killing of the pathogenic bacterium, Sta- 
phylococcus aureus, by AM from MS but not TS (41 ); (3) a reduction in basal super- 
oxide production by AM from MS (in contrast to an increase in basal superoxide 
generation by AM from TS) and an apparent attenuation by AM from marijuana smokers 
of the stimulated production of superoxide by AM from concomitant smokers of both 
tobacco and marijuana (40); (4) an impairment in the generation of nitric oxide by AM 
from MS (but not TS) that parallels their impairment in bactericidal activity (42); (5) 
a reduction in production of pro-inflammatory cytokines, tumor necrosis factor (TNF)- 
a and granulocyte macrophage-colony-stimulating factor (GM-CSF), by AM from 
MS when stimulated with bacterial lipopolysaccharide (41); and (6) an impairment in 
tumoricidal activity by AM from MS (41). A more detailed description of the effects 
of marijuana and THC on the function of AM and other immune cells and the likely 
clinical consequences of these immunological effects is provided below. 



Effects of Marijuana on Immune Defenses 



261 



Table 3 

Evidence Supporting Carcinogenic Effects of Marijuana 

• Increased concentrations of pro-carcinogenic polycyclic aromatic hydrocarbons (PAHs), 
including benzo-[a]-pyrene, in the tar phase of marijuana smoke compared to tobacco 
smoke (3,4,7) 

• Fourfold increase in lung deposition of tar from marijuana smoke as compared to tobacco 
smoke mainly as a result of the differences in cigarette filtration and smoking technique (6) 

• Activation of the cytochrome P4501A1 gene by THC, potentially enhancing the transfor- 
mation of PAHs into active carcinogens (7) 

• Accelerated malignant transformation in hamster lung explants exposed to marijuana 
smoke for up to 2 years (43) 

• Premalignant histopathological alterations in bronchial biopsies from smokers of mari- 
juana only, including metaplastic and dysplastic changes in the bronchial epithelium (35) 

• Overexpression of cell proteins associated with malignant transformation in the bronchial 
epithelium of habitual smokers of marijuana (36) 

• Systemic administration of A 9 -tetrahydrocannabinol accelerates the growth of non-small- 
cell lung cancer cells implanted into immunocompetent mice (44) 

• Case series reporting a disproportionately high percentage of chronic marijuana smokers 
in young patients (<45 years) diagnosed with upper airway or lung cancer (45-49) 

• Conflicting case-control studies demonstrating either a significantly increased risk (51) or 
no increased risk (52) of upper airway cancer in association with marijuana smoking 

• Evidence from a case-control study of an increased risk for developing lung cancer in 
association with the combined use of cannabis (hashish) and snuff (tobacco), but not with 
hashish alone (53) 



4. Potential Effects of Marijuana on Respiratory Carcinogenesis 

Several lines of evidence suggest that marijuana smoking may be a risk factor 
for the development of respiratory cancer (Table 3). First, the tar phase of marijuana 
smoke contains more of some pro-carcinogenic polycyclic aromatic hydrocarbons, 
including benz[a]pyrene, than the tar collected from tobacco cigarettes (3,4,7). Sec- 
ond, because of the manner in which marijuana cigarettes are smoked, approximately 
fourfold more of the particulate phase of the smoke (tar) is deposited in the human 
respiratory tract than occurs during tobacco smoking (6). This enhanced lung deposi- 
tion during marijuana smoking, combined with the high concentration of known car- 
cinogens in marijuana smoke, significantly magnifies the level of exposure to 
carcinogens from each marijuana cigarette. Third, THC can interact with the aryl 
hydrocarbon receptor and, independent of other components in the smoke, activate 
transcription of cytochrome P4501A1 (7). Cytochrome P4501A1 is involved in the 
biotransformation of polycyclic aromatic hydrocarbons into active carcinogens and 
plays a central role in the development of lung cancer. Fourth, hamster lung explants 
exposed to marijuana smoke for up to 2 years exhibited abnormalities in cell growth 
and accelerated malignant transformation (43). Fifth, bronchial biopsies from habitual 
marijuana smokers overexpressed surrogate endpoint markers of pretumor progres- 
sion, as already described (36). Sixth, non-small-cell lung cancer cell lines implanted 
into immunocompetent mice displayed accelerated growth when the animals were 



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given intraperitoneal injections of THC (44). Tumors and splenic tissue from these 
THC-treated mice overproduced immunosuppressive cytokines (interleukin [ILJ-10 
and transforming growth factor [TGF]-(3) and underproduced immunostimulatory 
cytokines (IL-2 and interferon [IFN]-y) compared with vehicle-treated mice. When 
the tumor growth experiments were repeated in the presence of a selective CB 2 an- 
tagonist, SR144528, the augmentation of tumor cell growth by THC was blocked. 
These findings suggest that THC accelerates tumor growth by a cytokine-dependent 
and CB 2 receptor-mediated mechanism that impairs the development of antitumor 
immunity. 

Although strongly suggesting that marijuana smoking is carcinogenic, these find- 
ings are not definitive proof that it is a clinically significant cancer risk factor. Addi- 
tional support for this conclusion is provided by several small case series, each reporting 
an unusually high proportion of marijuana smokers among young individuals (<40- 
45 years) in whom respiratory tract cancers have been diagnosed (45-49). The few 
controlled epidemiological studies that have addressed this issue, however, have revealed 
conflicting results. A large cohort study of participants in a health maintenance organiza- 
tion (n = 65,000) failed to show an association between marijuana smoking and the 
development of tobacco-related cancers (50). Interpretation of this study was limited 
by the fact that the participants were relatively young at the end of follow-up and 
relatively few cancers had therefore developed (50). A case-control study (n = 173 
head and neck cancer cases, 176 controls) found that a history of daily or near-daily 
marijuana smoking was associated with a 2.6-fold greater risk (95% confidence inter- 
val [CI] 1 . 1-6.6) for developing head and neck cancer after controlling for other known 
risk factors, such as tobacco smoking and alcohol use (51). Moreover, a dose-response 
relationship was noted, and the risk of marijuana smoking for the development of 
cancer was even higher among younger individuals (<55 years). In contrast, however, 
another case-control study of 407 cases of oral squamous cell cancer and 615 controls 
failed to find an association with marijuana use (odds ratio [OR] = 0.9, CI 0.6-1.3), 
even among younger, heavier, and longer-term marijuana smokers (52). A case-con- 
trol study conducted in Morocco, including 118 lung cancer cases and 235 controls, 
found that the combined use of hashish and snuff was associated with a 6.67-fold 
greater risk (95% CI 1.65-26.90) for developing lung cancer, while the risk was much 
lower for the use of hashish without snuff (1.93-fold [95% CI 0.57-6.58]), suggesting 
possible synergism between the effects of cannabis and tobacco on respiratory car- 
cinogenesis (53). A recently published case-control study of risk factors for oral can- 
cer in young people (<45 years) from the United Kingdom, which included 116 cases 
of squamous cell cancer of the oral cavity and 207 matched controls, failed to impli- 
cate cannabis use as a risk factor (54). On the other hand, a recently reported popula- 
tion-based case-control study of incident cases of cancers of the lung (n = 611) and 
upper aerodigestive tract (oral cavity, pharynx, and esophagus) (n = 601), along with 
1040 cancer-free population controls, from Los Angeles County did not find any posi- 
tive association between marijuana use (including heavy lifetime use, i.e., a cumula- 
tive total of > 10,950 joints) and the risk of lung or upper aerodigestive tract cancers 
after controlling for potential confounders (including tobacco use) (54a). Moreover, 
no interactions were observed between the effects of marijuana and tobacco. These 



Effects of Marijuana on Immune Defenses 



263 



results suggest that any possible association between marijuana use and respiratory 
cancer may be below practically detectable limits for typical levels of marijuana use. 

5. Effects of Marijuana and THC on Immune Defenses 

5.1. Cannabinoid Receptors on Peripheral Blood Leukocytes 

Marijuana smoking and purified THC were first proposed as immune modula- 
tors in the 1970s when abnormal leukocyte proliferation was observed in spleen cells 
collected from THC-treated animals (55) and in peripheral blood mononuclear cells 
collected from a sample of chronic marijuana smokers (56). However, similar find- 
ings were not reported in other clinical studies (57,58), and it was not until the discov- 
ery of the two different cannabinoid receptors that interactions between cannabinoids 
and the immune system began to be investigated in detail (59-62). Both CB, and CB 2 
are seven transmembrane G protein-coupled receptors that block forskolin-induced 
accumulation of intracellular cyclic adenosine 3',5'-monophosphate (cAMP) when 
activated (63). They have also been linked to a number of other signaling events, 
including changes in intracellular calcium, protein kinases, and nuclear factor for 
immunoglobulin K chain (NF-kB). Whereas CB, receptors are expressed at high 
levels in the central nervous system and mediate the psychotropic and behavioral ef- 
fects associated with marijuana use, CB, receptors are expressed mainly in peripheral 
tissues and primarily by leukocytes. Of the two cannabinoid receptor subtypes, mes- 
senger RNA (mRNA) encoding for the CB, receptor is present in mouse spleen at 
levels 10- to 100-fold higher than those of mRNA encoding for CB! (62,64). The CB 2 
receptor is also preferentially expressed in human leukocytes, where mRNA encoding 
for it is present at approximately threefold higher levels than mRNA encoding for CB, 
(65). Within human leukocytes, B-cells express several-fold higher levels of CB 2 recep- 
tor protein than monocytes, which express higher levels than those found in T-cells 
(62,65,66). The presence of these two receptor subtypes and their differential expres- 
sion in the brain (CB,) and on immune cells (CB,) suggests that endogenous cannab- 
inoids are part of a unique neuroimmune axis. 

To determine if cannabinoid receptors are activated on leukocytes in response to 
marijuana use, researchers from the University of South Florida and from the UCLA 
School of Medicine collected and examined peripheral blood samples from habitual 
marijuana users and nonsmoking control subjects (65). mRNA encoding for both CB, 
and CB 2 were evaluated by reverse transcriptase-polymerase chain reaction (RT-PCR) 
assays. A consistent and significant increase in expression of mRNA encoding for 
both CB, and CB 2 was observed in blood cells collected from marijuana smoking 
subjects, consistent with drug-induced receptor stimulation and potential regulation 
of host immune defenses (65). There is also evidence that activation of immune cells 
regulates expression of cannabinoid receptors in a reciprocal manner. When human 
B-cells were activated via their cell surface CD40 receptors, a reproducible increase 
in CB, receptor mRNA and cell surface protein occurred within 24 hours, with tran- 
scripts encoding for CB, increasing six- to eightfold (67). Gardner et al. (68) carried 
out similar studies using human peripheral blood T-cells. T-cells activated with an 
immobilized anti-CD3 monoclonal antibody that activates the T-cell receptor were 



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Table 4 

Associations Among Marijuana, THC, and Altered Immune Defenses 

• Human leukocytes express type 1 and type 2 cannabinoid receptors (CB, and CB 2 ), with 
expression of CB 2 higher than expression of CB[ (59-62,64-68) 

• mRNA encoding for both CB, and CB 2 was found to be increased in peripheral blood 
leukocytes collected from marijuana smokers when compared to samples collected from 
nonsmokers, suggesting cannabinoid receptor activation in response to marijuana smoking 
(65) 

• Systemic administration of A 9 -tetrahydrocannabinol (THC) to mice decreased the produc- 
tion of T-helper type 1 (Thl) cytokines (interleukin [IL]-2, interferon [IFN]-y) and 
increased the production of Th2 factors (IL-4, IL-10, and transforming growth factor 
[TGF]-(3), resulting in a suppression of T-cell immunity and increased susceptibility to 
opportunistic infections and the growth of implanted cancer cells (44,74,75) Epidemio- 
logical studies suggest an increased risk for bacterial pneumonia, opportunistic infections, 
and Kaposi's sarcoma in HIV- seropositive individuals who smoke marijuana compared to 
individuals who do not (83-85) 

• Alveolar macrophages (AM) recovered from the lungs of habitual marijuana smokers 
were found to be deficient compared to AMs recovered from the lungs of nonsmokers or 
tobacco smokers in their production of inflammatory cytokines, phagocytosis, antibacte- 
rial killing, and capacity to produce both superoxide anion and nitric oxide (40-42) 

• The inability of marijuana-exposed AM to express nitric acid synthase (iNOS) and kill 
pathogenic bacteria was reversed by treatment with granulocyte macrophage-colony- 
stimulating factor and IFN-y (42) 

• Human T-cells exposed to THC in vitro produced less IL-2 and IFN-y, but more IL-4, 
resulting in an imbalance between Thl and Th2 cytokines and an inhibition of T-cell acti- 
vation (86) 



examined for changes in their expression of CB, receptor protein by Western blots. T- 
cell activation was associated with an upregulation of CB 2 and with the induction of 
TGF-(3, an effect enhanced by THC in a CB 2 -dependent manner. Collectively, these 
studies demonstrate the potential for a bidirectional interaction between cannabinoid 
receptor expression and human B- and T-cell activation. Comprehensive reviews of 
the interaction between cannabinoids and immune function and the role of cannab- 
inoid receptors in this process were recently published by several authors, including 
Klein (10,69, 70), Cabral and Dove Pettit (71 ), Salzet (72), and Berdyshev (73 ). Rather 
than recapitulating these reviews, the following sections focus on evidence linking 
THC to immune regulation in drug-exposed animals and in human cells exposed to 
either purified THC in vitro or in vivo following marijuana use (Table 4). 

5.2. THC Alters Cytokine Balance and Suppresses 
Host Immunity in Animal Models 

Two well-designed mouse models have provided important insight into the po- 
tential impact of THC on immune responses (44,74,75). In one study, BALB/c mice 
were treated with a single intravenous dose of THC (4 mg/kg) before infection with a 
sublethal inoculation of Legionella pneumophila, a facultative intracellular bacterium 
that produces pneumonia in susceptible patients (74). When challenged 3-4 weeks 



Effects of Marijuana on Immune Defenses 



265 



later with a lethal inoculation of L. pneumophila, control mice survived and demon- 
strated L. pneumophila-specific T-cell proliferation and cytokine production. In con- 
trast, a high percentage of mice pretreated with THC during the immunization phase 
died following rechallenge, and their T-cells failed to proliferate in response to L. 
pneumophila antigen in vitro. T-cells, and the cytokines that they produce, serve as 
critical regulators of cell-mediated immunity. T-cells producing type 1 cytokines (Thl), 
including IL-2 and IFN-y, stimulate macrophage and T-cell effector function and pro- 
mote cell-mediated immunity (76). In contrast, T-cells producing primarily type 2 
cytokines (Th2), such as IL-4 and IL-10, suppress cell-mediated immunity and pro- 
mote humoral and allergic responses. Hypothesizing that THC might mediate its adverse 
effects by disrupting Thl/Th2 balance, additional experiments were performed. 
Exposure to THC was found to downregulate the production of antilegionella anti- 
body of the immunoglobulin-G (IgG) 2a subclass, associated with cell-mediated immu- 
nity, and increase antibody of IgG, subclass, associated with a Th2 response (74). In 
vitro, control splenocytes activated with immobilized anti-CD3 antibody secreted pri- 
marily IFN-y with little IL-4. However, splenocytes activated in the presence of THC 
produced less IFN-y, and more IL-4 in a dose-dependent manner. The capacity for 
THC to block immunity against L. pneumophila, promote an immunoglobulin sero- 
type switch from IgG 2a to IgG,, and alter the balance of memory T-cells producing 
Thl and Th2 cytokines, provided the first evidence that cannabinoids and cannabinoid 
receptors might act as Th2 inducers. 

In follow-up experiments, THC was examined for its impact on cytokine pro- 
duction during the initial immunization phase (75). Consistent with its role as a Th2 
inducer, pretreatment with THC resulted in lower serum concentrations of IL-12 and 
IFN-y within hours after sublethal infection with L. pneumophila. THC also stimu- 
lated splenocytes to secrete higher levels of IL-4. Additional experiments revealed a 
downregulation in the expression of mRNA encoding for the IL-12 receptor and thus 
a coordinated suppressive effect of THC on the production and function of Thl -induc- 
ing cytokines. Employing the same model, mice were treated with either CB, or CB 2 
selective receptor antagonists (SR141716A or SR144528, respectively) before admin- 
istration of THC. Administration of either receptor antagonist blocked the effects of 
THC on the production of Thl cytokines, suggesting that both cannabinoid receptors 
participate in the immunological consequences mediated by THC (75). Because CB, 
receptors are expressed primarily in the central nervous system, it was hypothesized 
that ligation of CB, receptors by THC acts on the hypothalamic-pituitary-adrenal axis, 
resulting in secondary immunoregulation by corticosteroids (77). Corticosteroids are 
known to regulate Thl/Th2 balance, favoring the development of Th2 responses (78). 
Alternatively, because both CB, and CB 2 are expressed on leukocytes, THC might 
mediate its effects directly by either one or both of these receptors. 

The second animal model was developed by Zhu et al. (44) to examine the effects 
of THC on the host response to a tumor challenge. Immune function plays a central 
role in limiting tumor growth (79), and disruption of Thl/Th2 cytokine balance by the 
tumor plays an opposing role in promoting tumor growth (80). As such, it was hypoth- 
esized that the regulatory effects of THC on Thl/Th2 balance, with a decrease in Thl- 
cells and an increase in Th2-cells, might disrupt host antitumor immunity and promote 



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tumor growth. Mice were treated with daily intraperitoneal injections of THC (5 mg/kg) 
for 4 days each week and then challenged with subcutaneous tumor implants. As 
hypothesized, mice receiving THC experienced a more rapid rate of tumor growth. By 
the end of 5-6 weeks, tumors in control animals had grown to 3000-4000 mm 3 in size, 
whereas tumors implanted into animals treated with THC averaged 12,000-13,000 
mm 3 . Similar results were observed in two different lung cancer models, one employ- 
ing Line 1 alveolar cell carcinoma implanted into BALB/c mice and the other using 
Lewis lung carcinoma cells implanted into C57B1/6 mice. Because there was no direct 
effect of THC on the proliferation of either tumor in vitro, and administration of THC 
had no effect when tumors were implanted into immunodeficient mice, these studies 
suggested that THC enhanced tumor growth by disrupting immune function in vivo. 
As reported in the L. pneumophila model, splenocytes from THC-treated mice pro- 
duced less IFN-y. Zhu et al. (44) also examined splenocytes for their production of IL- 
10, a regulatory Th2 cytokine (81), and TGF-(3, another immunosuppressive factor 
known to downregulate the production of IFN-y (82). Production of both IL-10 and 
TGF-(3 were increased roughly twofold in the spleen and at the tumor site in animals 
receiving THC. More importantly, administration of neutralizing antibody specific 
for either IL-10 or TGF-(3 completely neutralized the impact of THC on tumor growth. 
These studies demonstrated for the first time that THC can regulate antitumor immu- 
nity by increasing the production of suppressive cytokines. Finally, blocking studies 
with SR144528, a selective CB 2 receptor antagonist, confirmed a receptor-mediated 
pathway. 

5.3. Impact of THC on Human Immune 
Responses and T-C ell Activation 

In addition to animal models, there are several epidemiological studies suggest- 
ing that marijuana smoking can predispose to the development of opportunistic infec- 
tions and cancer. Tindall et al. (83) collected careful drug use histories from 386 
HIV-positive individuals and observed a significantly more rapid progression from 
HIV infection to AIDS in those who smoked marijuana. Similarly, Newell and associ- 
ates (84) found marijuana use to be associated with the acquisition of opportunistic 
infections and/or Kaposi's sarcoma in patients with HIV (OR 3.7). Caiaffa et al. (85) 
also observed that the smoking of illicit drugs, including marijuana and/or cocaine, 
was statistically associated with the development of bacterial pneumonia in HIV-posi- 
tive individuals (OR 2.24). More recently, marijuana use was identified in one large 
study as an independent risk factor for the development of head and neck cancer (51). 

To evaluate the impact of THC on human immune responses, Yuan et al. (86) 
purified T-cells from the blood of healthy volunteers and stimulated them ex vivo 
with antigen-presenting cells in the presence or absence of THC. THC inhibited T-cell 
proliferation in a dose-dependent manner, with 5 (ig/mL inhibiting activation by an 
average of 53% (range 28-79%) compared with control cells. Hypothesizing that this 
effect was associated with a change in the balance of Thl and Th2 cytokines, superna- 
tants were harvested from the T-cell cultures and examined for the presence of IFN-y 
and IL-4. IFN-y concentrations were reduced on average by 50%, whereas IL-4 levels 
were increased on average to 1 10%, resulting in a significant shift in Thl/Th2 cytokine 



Effects of Marijuana on Immune Defenses 267 



Control T + 1L-12 „ + THC 




Fig. 4. Tetrahydrocannabinol (THC) shifts the capacity for activated T-cells to pro- 
duce T-helper type 1 (Th1 ) and T-helper type 21 (Th2) cytokines. Purified human T- 
cells were activated with a combination of monoclonal antibodies directed against 
the T-cell receptor (CD3) and costimulatory molecules (CD28) in the presence of 
control medium (left panel) or medium supplemented with interleukin (IL)-12 (10 ng/mL, 
middle panel) or THC (5 ug/mL, right panel). Cells were permeabilized, and the 
production of interferon (IFN)-y, a Th1 cytokine, and IL-4, a Th2 cytokine, was 
detected in each cell by flow cytometry. IL-12 increased the Th1/Th2 ratio, whereas 
THC decreased the production of IFN-y and the Th1/Th2 ratio. 

balance similar to that observed in animal models (44,74,75). When examined at the 
single cell level, THC decreased both the number of T-cells producing IFN-y and the 
average cytokine production per cell (Fig. 4). CD4 + and CD8 + T-cells were both equally 
suppressed. The impact of THC on the subsets was also examined at the level of mRNA 
expression using a ribonuclease protection assay to simultaneously assay for both Thl 
(IL-2, IFN-y) and Th2 (IL-4, IL-5) cytokines. Consistent with the results obtained by 
enzyme-linked immunosorbent assay and single cell analyses, mRNA encoding for 
IFN-y and IL-2 was reduced by 21-48% in cells treated with 5 txg/mL THC, and mRNA 
encoding for IL-4 and IL-5 was increased by 1.5- to 11.2-fold. Pretreatment with 
SR144528, a CB 2 -selective antagonist, prevented the majority of the THC-mediated 
effects, whereas there was little response to AM251, a selective CB[ antagonist. This 
work suggests a strong correlation between murine models and human studies, with 
THC acting via cannabinoid receptors to suppress antigen-specific T-cell activation 
and skew responding T-cells toward a Th2 profile (86). 

As in the mouse model by Zhu et al. (44), THC also upregulates the production 
of TGF-(3 when human T-cells are activated by immobilized anti-CD3 (68). TGF-(3, 
although not a classic Th2 cytokine, inhibits T-cell proliferation, suppresses produc- 
tion of IL-2 and IFN-y, and antagonizes the activation of both lymphocytes and mono- 
cytes. As little as 50 ng/mL of THC increased the production of TGF-(3 two- to threefold, 
and 5 \iglmL of THC increased the release of TGF-(3 protein fivefold. To evaluate the 
role of cannabinoid receptors in this response, human T-cells were pretreated with 
either pertussis toxin, forskolin, or methylxanthine before activation in the presence 
of THC. Inactivation of G protein-coupled receptors by pertussis toxin, activation of 
adenyl cyclase by forskolin, and inactivation of phosphodiesterase activity by 



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methylxanthine all blocked the capacity for THC to induce TGF-(3 consistent with 
signaling via cannabinoid receptors. Selective CB, or CB 2 receptor antagonists were 
then used to confirm that signaling was mediated via the CB 2 receptor. It is entirely 
possible that upregulation of TGF-(3 by THC mediates many of its immunological 
consequences on human cells, as it does on mouse cells, but experiments to test this 
hypothesis have not yet been carried out. 

5.4. Immunological Suppression of Alveolar Macrophages 
in the Lungs of Habitual Marijuana Smokers 

The finding that peripheral blood leukocytes collected from marijuana smokers 
express higher than normal levels of CB, and CB 2 mRNA (65), and that THC mediates 
distinct immunoregulatory effects when cultured with human leukocytes in vitro 
(68,86), provide only indirect evidence that marijuana smoking is associated with 
immunological consequences. The most compelling and direct evidence is provided 
by studies with AM recovered directly from the lungs of habitual marijuana users 
(Table 2; refs. 41 and 42). AM are the primary immune cells residing in the distal air 
spaces of the lung, where they take up and retain large amounts of inhaled tar (39). As 
previously described, AM recovered from the lungs of marijuana smokers were found 
to be significantly impaired in their ability to secrete pro-inflammatory cytokines and 
to phagocytose and kill S. aureus, whereas AM from tobacco smokers performed nor- 
mally in these studies (41). It is very likely that THC, which is present only in the tar 
generated from marijuana smoke, accounts for these functional abnormalities. 

THC can alter specific cytoskeletal components involved in phagocytosis (tubu- 
lin and actin) and inhibit macrophage-mediated phagocytosis in vitro (87). In addition 
to producing defects in phagocytosis, THC can also impair the production of nitric 
oxide (NO), a reactive nitrogen intermediate that serves as an important effector mol- 
ecule in bacterial killing (88). Using murine macrophage cell lines, several investiga- 
tors have demonstrated that THC suppresses lipopolysaccharide-induced production 
of NO and subsequent antibacterial or antitumor activity (89-91). This effect is medi- 
ated by cannabinoid receptors, involves inhibition of both cAMP and the NF-KB/Rel 
family of transcription factors, and blocks the induction of mRNA encoding for 
inducible nitric oxide synthase (iNOS) (91). 

Inhaled THC appears to mediate the same effects in the lungs of marijuana smok- 
ers. The etiology for this antimicrobial deficit was first suggested by inhibitor studies 
using N G -monomethyly-L-arginine monoacetate (NGMMA), an inhibitor of NOS (41 ). 
The addition of NGMMA to cultures containing AM from nonsmokers and tobacco 
smokers inhibited their antibacterial killing activity, but this compound had no effect 
when added to cultures containing AM from marijuana smokers. S. aureus, and its 
isolated cell wall constituent protein A, are known to induce NO when used to stimu- 
late murine cells in vivo and/or in vitro (92,93). The investigators hypothesized that S. 
aureus induced iNOS when added to cultures with AM from nonsmokers or smokers 
of tobacco only, resulting in potent antimicrobial activity, but not when added to cells 
recovered from marijuana smokers. To test this hypothesis, they used semi-quantita- 
tive RT-PCR to measure mRNA levels encoding for iNOS in resting AM and follow- 
ing co-culture with S. aureus (42). Release of NO was also determined by the 



Effects of Marijuana on Immune Defenses 



269 



accumulation of nitrite in the culture supernatant, and the impact on bacterial killing 
was also measured. Exposure to S. aureus induced the expression of iNOS and the 
production of nitrite in AM from control smokers and tobacco-only smokers, but not 
in AM from marijuana smokers. Resting macrophages must be primed with inflam- 
matory cytokines, such as TNF-a, IFN-y, or GM-CSF, in order to upregulate expres- 
sion of iNOS. Interestingly, production of NO and restoration of efficient antimicrobial 
killing by cells from MS were restored following the addition of these pro-inflamma- 
tory cytokines (IFN-y or GM-CSF) to the S. aureus killing assay. In contrast, the addi- 
tion of cytokines had no effect on the expression of iNOS or bacterial killing when 
added to cells from nonsmokers or smokers of tobacco only. These findings suggest 
that impairment in the bactericidal activity of AM from marijuana smokers was a 
result of a THC-related inhibition of key pro-inflammatory cytokines that are needed, 
in turn, to induce iNOS. Consistent with this hypothesis, Baldwin et al. (41) found that 
lipopolysaccharide, a bacterial wall component involved in macrophage activation, 
failed to stimulate normal release of TNF-a, IL-6, or GM-CSF from AM recovered 
from the lungs of marijuana smokers. AM recovered from tobacco smokers produced 
normal levels of these cytokines and, as reported above, exhibited normal induction of 
NO and normal antibacterial activity. The clinical implications of these findings are 
that regular marijuana smoking may compromise the lung's defense against infection 
by impairing the antimicrobial function of AM and the production of pro-inflamma- 
tory cytokines required for immune activation. 

6. Summary 

The smoke generated during the pyrolysis of cannabis contains not only a high 
concentration of THC, but also a large number of toxic gases and particulates similar 
to tobacco smoke. The effects on the lung are therefore complex. Whereas THC can 
produce short-term bronchodilation by relaxing airway smooth muscle, heavy habitual 
smoking of marijuana is associated with mainly adverse pulmonary consequences. 
These include symptoms of acute and chronic bronchitis, endoscopic evidence of air- 
way injury, lung inflammation, and extensive histopathology and immunohistological 
evidence of dysregulated growth of the tracheobronchial epithelium. These damaging 
effects of marijuana smoking are magnified by (1) its high concentration of polycyclic 
aromatic hydrocarbons (which act as pro-carcinogens), (2) the enhanced deposition of 
tar because of the manner in which marijuana is smoked, and (3) the biological effects 
of THC on respiratory epithelial cells, which include oxidant stress, mitochondrial 
dysfunction, induction of cytochrome P4501A1, and inhibition of apoptosis. These 
features raise concerns that marijuana smoking may predispose to respiratory malig- 
nancy. However, epidemiological evidence linking marijuana use and respiratory cancer 
is at present inconclusive. Moreover, in contrast to the known relationship between 
regular tobacco smoking and the development of COPD, cohort studies have yielded 
inconsistent findings with the respect to the impact of regular smoking of marijuana 
on the development of chronic airways obstruction. Habitual use of marijuana has 
also been shown to produce abnormalities in the structure and function of AM, key 
cells in the lung's immune defense system. Specifically, AM from regular marijuana 



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users are impaired with respect to antimicrobicial and tumoricidal activity, production 
of immunostimulatory cytokines, and generation of iNOS and NO, an important effector 
molecule in microbial killing. These changes in AM are consistent with the effects 
observed when immune cells are exposed to THC in vitro and in vivo in animal mod- 
els. Both CB, and CB 2 receptors are expressed on immune cells and blood samples 
collected from marijuana smokers suggest that these receptors are stimulated by mari- 
juana smoking. Acting primarily through CB 2 , THC suppresses T-cell activation and 
alters the production of cytokines, resulting in a predominance of immunosuppressive 
factors such as IL-10 and TGF-(3 and a reduction of immunostimulatory cytokines 
including IL-2, IL-12, and IFN-y. In animal models THC impairs the immune response 
to both opportunistic infections and cancer. Epidemiological studies suggest that mari- 
juana smoking may have similar immunosuppressive effects in humans. Taken together, 
these findings may have important clinical implications, including the possibility of 
(1) an increased risk of opportunistic infections, especially in already 
immunocompromised patients as a result of AIDS, organ transplantation, or chemo- 
therapy for cancer and (2) an increased risk of developing respiratory tract cancer, 
possibly in synergism with the risk from concomitant tobacco use. However, results 
of epidemiological studies are thus far mixed with regard to the actual occurrence of 
these potential clinical consequences of marijuana on the lung and host immune de- 
fenses. Other epidemiological study designs or approaches may be necessary to clarify 
whether marijuana is truly associated with these risks. 

A CKNOWLEDGMENT 

Research and writing supported by the National Institute on Drug Abuse grant 
#R37DA03018. 

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Chapter 12 



Marijuana and Driving Impairment 

Barry K. Logan 

1. Effects of Marijuana 

After alcohol, marijuana is the most popular recreational drug in North America. 
Its effects are largely predictable in type, but not in degree, although they do appear in 
a roughly dose-dependent manner. The effects discussed here make a very convincing 
case for the potential for marijuana to impair driving, although as noted, the extent to 
which that potential is realized in a given case will be related to many other factors. 

1.1. Getting "High" 

People variously use marijuana for its exhilarating, relaxing, hallucinogenic, 
antinausea, and soporific effects. 

Marijuana is most frequently smoked and less frequently eaten in baked goods or 
drunk as an infusion. Cannabis products, including marijuana, hashish, and hashish 
oil, can be ingested orally, in tea, or baked into brownies. The effect profile from oral 
ingestion is much longer, taking longer for the drug to be absorbed and for the active 
A 9 -tetrahydrocannabinol (THC) to be distributed. The drug is likely subject to 
enterohepatic cycling when orally ingested, further complicating its kinetics. Metabo- 
lite concentrations are often highly elevated. It is not uncommon for the acute effects 
to last for 24 hours following oral ingestion. Oral use is also more frequently associ- 
ated with adverse effects, such as paranoia, panic, depression, and irritability. Cur- 
rently available tests for blood or urine will not allow discrimination of the route of 
administration. 

Following smoking, marijuana effects appear within 5-10 minutes. The lower- 
grade effects are remarkably similar to those resulting from alcohol consumption: 
relaxation, social disinhibition, and talkativeness. This disinhibition leads to users per- 
ceiving the drug effects as being mildly stimulatory at low doses. Users report the 

From: Forensic Science and Medicine: Marijuana and the Cannabinoids 
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey 

277 



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experience as producing a general sense of well-being, which can rise to the level of 
exhilaration or euphoria. It is described as a blissful state of reverie, fantasy, free- 
flowing thought, and clarity. The senses are heightened, with colors, smell, touch, 
taste, and body perception being enhanced. Cravings for food are common. Bouts of 
uncontrollable spontaneous laughter or giggling are regularly seen, with even com- 
mon events appearing to be funny or amusing. 

The perceptual effects of marijuana use have an association with driving impair- 
ment at least in part as a result of their distracting nature. The degree to which some- 
one is absorbed in his or her drug experience will affect his or her inclination to engage 
fully in other demanding tasks such as driving. The degree of effect will differ from 
individual to individual and can be significantly affected by the setting. 

1.2. Physiological Effects 

The physiological effects of marijuana use are more tenuously related to driving; 
however, they are useful indicators in assessing a person for recent marijuana use. 
THC is a vasodilator, and within minutes of smoking marijuana, peripheral vasodila- 
tion leads to a precipitous drop in blood pressure and a reflex increase in heart rate. 
Users can feel dizzy or faint until homeostasis is restored. The dilatory effects of the 
drug on the capillaries in the sclera produce a distinctive reddening of the eyes, giving 
them a bloodshot appearance. Users usually report a dry throat and mouth. Among the 
other effects on the eyes are loss of convergence or ability to cross, hippus (an inter- 
mittent change in the size of the pupil occurring without external stimuli), and rebound 
dilation following changing light conditions, in which the pupil size will oscillate 
before stabilizing. Nystagmus, or the ability of the eye to track smoothly, is affected 
by marijuana and becomes more prominent under conditions of very high or repeated 
dosing. 

Although these effects are not indicators of impairment per se, this characteristic set 
of symptoms can be relied on by police officers or medical personnel to make a connection 
between an individual's appearance of intoxication and recent marijuana use. 

1.3. Cognitive and Psychomotor Effects 

Driving is a complex task requiring the integration of various cognitive and psy- 
chomotor skills. Cognitive skills are those related to the processes of knowing, think- 
ing, learning, and judging. For driving, these effects include memory, perceptual skills, 
cognitive processing and task accuracy, reaction time, and sustained and divided 
attention. 

Impairment of short-term memory and learning impairment following marijuana 
use is probably the most frequently reported and validated behavioral effect of mari- 
juana use, and one for which there is the most consistent evidence. The link between 
memory impairment and driving impairment is, however, difficult to make convinc- 
ingly. The strongest argument is the contribution of memory impairment to focus and 
selective attention. A clear recollection of recent events contributes to organizational 
and planning ability and promotes goal-directed behavior and action, allowing the 
subject to devote available cognitive capacity more efficiently to the driving task. 

The user's perception is altered with respect to the passage of time, which appears 
to pass more quickly relative to real time. Impairment in perception of speed and 



Marijuana and Driving Impairment 



279 



distance may be related to the time distortion. Laboratory studies have shown that 
cannabis users lose the perceptual ability to identify simple geometric figures within 
more complex patterns when intoxicated. Such perceptual changes can influence a 
person's normal driving behavior in a potentially unsafe way. 

Simple tests of cognitive processing such as measures of associative ability (e.g., 
digit symbol substitution, Stroop color word test) have been shown to be adversely 
affected by acute cannabis use resulting in greater numbers of errors. The effect when 
compared to moderate doses of alcohol, however, is small. 

Reaction time effects are also present and are more significant at higher doses, 
but they are generally small compared with those observed with moderate doses of 
alcohol. Impairment indicators are more prominent in complex rather than simple 
reaction time tests, and subjects tend to perform more slowly and make more errors. 

Driving is a divided- attention task, and as such, laboratory assessments of divided 
and sustained attention performance have been scrutinized for evidence of effects. 
These tests show consistently that the greater the demands on cognitive processing 
ability, the more complex the tasks, and the more tasks to be attended to, the poorer 
marijuana-dosed subjects performed. This has important implications for marijuana 
and driving impairment and explains the findings in some of the on-road driving stud- 
ies discussed later. 

Driving demands various levels of attention, cognitive capacity, and psychomo- 
tor ability, depending on factors such as weather, road conditions, vehicle condition, 
other road user behavior, lighting, and city vs highway driving. The threshold demands 
of driver performance for satisfactory vehicle operation might be within the subject's 
ability under normal driving conditions, but if the demands change unexpectedly, or 
emergencies arise, or there is a confluence of demands occurring at once (merging 
traffic, signal failure, unfamiliar neighborhood, road construction, etc.), the driver's 
ability is surpassed and errors arise that result in a crash or bring the driver to the 
attention of the police. Peak cognitive impairment effects are reported to occur roughly 
40-60 minutes following smoking and typically last for about 2-3 hours. 

1.4. Hallucinations 

The effects noted on heightened awareness of colors, smell, touch, and taste can 
be enhanced to the point where they constitute hallucinations — perceptions of things 
or sensations that do not exist. Objects can appear to "melt" or to lose or change form. 
Synesthesias can occur in which, for example, sound or music can trigger visual or 
olfactory sensations. In most marijuana users who do experience these, they are more 
correctly characterized as pseudohallucinations in that the user is aware that the per- 
ception is unreal even while experiencing it. Nevertheless, hallucinations of any kind 
are distracting and absorbing and, when they occur, will impair attention and focus. 

Infrequently, flashbacks are reported where individuals will re-experience or viv- 
idly recall the experience of a previous marijuana "trip." This can be triggered by envi- 
ronmental cues or by readministration of marijuana or some other psychoactive drug. 

1.5. Other Adverse Reactions 

Although many of the effects discussed above have the potential to be detrimen- 
tal to driving, the adverse affects considered here are those not sought by the recre- 



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ational marijuana user (a "bad trip"). They are atypical, but can be related to the user's 
underlying frame of mind or mood, and are most commonly reported by naive users. 
These include dysphoria, tearfulness, extreme anxiety, mild paranoia, and panic. When 
this occurs, its relationship to impairment of driving is clear. Typically at higher doses 
or in naive users, sedation or sleepiness becomes a significant factor, and presumably 
users already tired would be more susceptible to this effect. 

1.6. Discussion 

Based on the above considerations, it is clear than in many respects marijuana 
has the ability to produce effects — both sought-after and incidental — that can affect 
the balance of skills and abilities needed to drive safely. These effects can vary in 
magnitude, but frequently when compared with effects of moderate dosing with alco- 
hol (e.g., the presumptive level for intoxication in many US states of 0.08 g ethanol/ 
100 mL blood), the impairing effects are less severe, even after the use of typical user- 
preferred doses. Additionally, the consistent observation that the impairing effects of 
marijuana after moderate use will dissipate in 2-3 hours limits the likelihood of police 
contact or crash involvement if the driver allows some time to pass between marijuana 
use and driving. The related ability of marijuana users to recognize the drug effect and 
take a less risky course of action also contributes positively to harm reduction. 

On balance, the empirical evidence suggests that impairment observed following 
recent marijuana use can very reasonably be ascribed to the drug. This is most likely 
when the drug use, if moderate, is within 3 hours of driving. Beyond this time frame, 
however, light to moderate marijuana use under normal demands of driving does not 
consistently generate impairment in driving skills that would come to the attention of 
the police or result in increased risk of crash involvement. 

2. Evidence of Marijuana Intoxication 

2.1. Diagnosis of Marijuana Use: 
Physiological and Psychomotor Effects 

According to the Drug Recognition Expert evaluation matrix used by police 
officers, characteristic symptoms of marijuana use include a lack of horizontal or ver- 
tical gaze nystagmus, pupil size dilated to normal, a lack of pupillary convergence, 
and pupils normally reactive to light. Pulse is usually elevated within the first few 
hours following use, and blood pressure is correspondingly elevated. Body tempera- 
ture will typically be normal. Speech may be slow or slurred, and muscle tone will be 
normal. Other clues include stale breath; sometimes users will have flakes or residue 
of marijuana in the mouth or a green discoloration of the tongue. The taste buds may 
be elevated as a result of irritation from the hot smoke. The user's eyes will typically 
be bloodshot because of the vasodilatory effects of THC on the capillaries of the sclera. 
The face may be similarly flushed, and subjects may be diaphoretic. Nystagmus is not 
typically present, although some studies do suggest an association between acute mari- 
juana use and nystagmus. 

Subjects may have short attention spans, express hunger (THC is an appetite 
stimulant), and giggle or laugh. If acutely intoxicated, users may also seem dazed, 



Marijuana and Driving Impairment 



281 



disengaged, or unconcerned. Because of the short distribution half-life of THC, users 
may also appear to sober up or improve in their performance and coordination during 
the first hour or two in custody. 

Field sobriety tests have been criticized for having been validated for alcohol 
and not for other drugs. The tests, however, are considered tests of impairment; that is, 
they are tests that a normal sober person can perform without much difficulty, but that 
a person impaired in cognitive and psychomotor skills cannot. Any errors in the test 
may therefore be considered indicators of impairment irrespective of its cause. A careful 
validation of the tests for marijuana has recently been performed in 40 subjects. 
Papafotiou et al. (1) evaluated the efficacy of the standardized field sobriety three-test 
battery on marijuana smokers. They applied the three tests — horizontal gaze nystag- 
mus, walk and turn, and one-leg stand — at 5, 55, and 105 minutes after smoking a 
placebo, 1.74%, or 2.93% THC content marijuana cigarette. The data are summarized 
in Table 1. 

The study showed dose-dependent increases in rates of impairment in the sub- 
jects, with the most pronounced effects closest to smoking. It also confirmed low rates 
of failure of 2.5-7.5% in nonintoxicated subjects. After 100 minutes, symptoms of 
impairment were beginning to diminish. The authors also noted a fourth category of 
head movements and jerks. Adding the head movements and jerks observations im- 
proved the diagnostic value of the tests by 5-20% and should be considered for future 
inclusion in a battery of tests for drug impairment. 

Individually, the walk-and-turn test elicited significant differences in performance 
between the marijuana and placebo conditions, but misses heel to toe, improper turn, 
and incorrect number of steps appeared almost as often in the placebo session as they 
did in the THC conditions and are therefore likely to be observed irrespective of drug 
consumption. Balance and ability to focus attention were impaired at all three time 
points. Of the three tests, the one-leg stand was the most significant at all three time 
points, with poorer performance being significantly related to the level of THC at all 
testing times, as was performance on all of the scored signs of this test except for 
hopping at Time 3. 

Overall, when impairment caused by drugs including marijuana is present, it 
apparently can be detected by the tests currently in widespread use by police officers. 
It is likely that these tests can be further refined to increase their effectiveness and 
sensitivity. 

2.1.1. Toxicological Tests 

Marijuana use can be demonstrated by a chemical or toxicological test. Toxico- 
logical tests for detection of marijuana use currently include hair, urine, blood, sweat, 
and oral fluid. Hair marijuana tests offer the possibility of looking at marijuana expo- 
sure over the time period during which the hair was growing. Hair grows at a rate of 
about 1 cm a month, and most commercial vendors offering hair testing will test a 3- 
cm (~3 month) section closest to the scalp. Upon request, a longer length can be tested, 
in sections if necessary, to assess patterns of use over the lifetime of the growth of the 
hair. This test has little applicability in assessing intoxication at any particular point in 



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Table 1 



Relationship Between Time After Smoking, Average Blood THC 
Concentration (ng/mL), and Percentage of Subjects Considered 
Impaired Under Standardized Field Sobriety Tests (SFSTs) 3 





Time 1 (0-5 min) 


Time 2 (50-55 min) 


Time 3 (100-105 min) 




Blood 


<V 

10 


Blood 


0/ 

/o 


Blood 


0/ 
10 


Dose 


THC 


impaired 


THC 


impaired 


THC 


impaired 


Placebo 





2.5 





7.5 





5 


1.74% THC 


55.5 


23 


6.8 


23 


3.7 


15 


2.93% THC 


70.6 


46 


6.2 


41 


3.2 


28 



THC, A'-tetrahydrocannabinol. 

Time 1 , min after smoking for blood sampling and 5 min for SFSTs; Time 2, 
50 min after smoking for blood sampling and 55 min for SFSTs; Time 3, 1 00 min 
after smoking for blood sampling and 1 05 min for SFSTs. 

From ref. 7. 



time, however, as would be relevant in an impaired driving investigation. If the subject's 
prior marijuana use became an issue, this approach could offer some qualitative insight. 

2.1.1.1. Toxicological Evidence: Urine 

As discussed in Chapters 5 and 9, THC is metabolized to 11-OH-THC and 11- 
carboxy-THC (THC-COOH). The latter compounds are glucuronidated and excreted 
in the urine. Substantial variation exists in the excretion patterns of marijuana me- 
tabolites in subjects' urine. THC metabolites appear in the urine in detectable amounts 
within 30-90 minutes following smoking, but they may not reach the levels needed to 
cause a positive response at typical thresholds used for screening. Many laboratories 
use the 50 ng/mL screening cutoff mandated for federal workplace urine drug testing, 
but one study showed that first void urine specimens after smoking a single 3.55% 
THC marijuana cigarette quantitated below that threshold in five of six subjects, at 
times ranging from 1 to 4 hours (mean 3.0 hours; ref. 2). In the same subjects, each 
smoking an identical 3.55% THC cigarette, peak urine concentrations varied consid- 
erably (29-355 ng/mL, mean 153 ng/mL), as did the time to peak (5.6-28 hours, mean 
13.9 hours). Similarly, urine specimens were confirmed positive by gas chromatogra- 
phy /mass spectrometry at a 15 ng/mL cutoff for 57-122 hours following this single 
use (mean 89 hours or 3.7 days). The same authors have reported similar results in 
other subjects (3). Using a lower threshold, for example, 20 ng/mL, was shown to be 
more effective in identifying use for a longer period of time and presumably for ear- 
lier detection of use in urine samples. 

Other workers have evaluated the time it took for urine samples to test consis- 
tently negative in chronic marijuana users (4). These authors identified an extreme 
case of a subject who took 77 days to produce 10 consecutive negative urine samples 
screened at a 20 ng/mL cutoff. Of the 86 subjects evaluated, the mean time to the end 
of their consecutive positive results at that threshold was 27 days. 

There are significant implications following from these and similar studies for 
the use of urine as the specimen in a driving-under-the-influence-of-drugs (DUID) 



Marijuana and Driving Impairment 



283 



setting. A specimen taken up to 3 hours after smoking marijuana may test negative for 
cannabinoids, depending on the screening threshold used and the potency of the mari- 
juana smoked, even though the subject would have experienced the peak effect within 
a few minutes and would have been under the influence of marijuana at the time of 
driving or arrest. Also, following single acute use by naive users, urine concentrations 
may peak, then drop below detectable levels over the space of a few hours. Con- 
versely, the presence of marijuana metabolites in a subject's urine may have resulted 
from drug use several days earlier, considerably after the impairing effects of the drug 
have passed. 

In summary, a positive urine test for THC-COOH cannot be used to infer either 
intoxication or marijuana use within any forensically useful time frame. At best, if 
coupled with objective observations of physiological signs and symptoms of mari- 
juana use and documentation of psychomotor impairment, it can substantiate an opin- 
ion that observed impairment was a result of marijuana use. 

2.1.1.2. Toxicological Evidence: Blood 

Blood or plasma* analysis of THC provides the most direct toxicological evi- 
dence of recent marijuana use and, consequently, of intoxication. There are several 
approaches to the interpretation of blood toxicological data. 

2.1.1.2.1. THC and THC-COOH Concentrations 

Because the effects of marijuana use have a relatively rapid onset when smoked, 
users can titrate the effects against the rate of administration to maximize the desir- 
able drug effects while minimizing the adverse effects. Various studies have attempted 
to identify a "user-preferred" dose of marijuana. These have established a typical user- 
preferred dose of about 300 Hg/kg, or about 21 mg in a 70-kg (154-lb) individual (7). 
In terms of what this translates to in marijuana cigarettes, that will depend on the THC 
content of the marijuana and the individual's smoking technique, with more efficient 
absorption achieved with deeper inhalation and breath holding. 

For context, a standard National Institute on Drug Abuse marijuana cigarette 
(weight 558 mg) having 3.58% THC content would deliver 20 mg of THC, although 
not all of that may be bioavailable, depending on the subject's smoking technique. 
Plasma concentrations of THC and THC-COOH from one study with different levels 
of dosing are shown in Table 2. 

Current street marijuana strength can vary considerably, from essentially zero to 
20% THC content or more; consequently, predicting THC concentration or impair- 
ment based on a history of how many "joints" were smoked is inadvisable. 

Peak blood or plasma THC concentrations occur within a few minutes of the end 
of smoking and begin a rapid decline as the drug distributes from the central compart- 
ment into tissues. There is widespread agreement that the peak effects of the drug 
occur after the blood concentration has peaked and begun to decline. Plasma THC 
concentrations of 2-3 ng/mL (equivalent to whole blood concentrations of 1-1.5 ng/ 



*Most pharmacokinetic studies have made measurements of THC and its metabolites in plasma, whereas 
in a forensic context whole blood is the most commonly analyzed specimen. The plasma-to-whole blood 
ratio for cannabinoids is approx 2:1 (5,6); therefore, when comparing whole blood concentrations to plasma 
concentrations, the plasma concentrations should be divided by 2. 



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Table 2 

Mean, Median, and Range of THC and THC-COOH Concentrations in Plasma of 14 
Subjects Under Various Dosing Conditions 



100ug/kg 200 ug/kg 300 ^g/kg 







f = 35 


f = 190 


f = 35 


f = 190 


f = 35 


f = 190 


THC 


Mean 


7.9 


0.7 


12.0 


1.0 


16.1 


1.5 




Median 


6.5 


0.9 


10.0 


1.1 


15.8 


1.5 




Range 


0.8-17.2 


0.0-1.3 


1.5-27.1 


0.0-2.7 


4.7-30.9 


0.4-3.2 


THC-COOH 


Mean 


8.2 


4.1 


12.2 


7.61 


15.3 


10.0 


(ng/mL) 


Median 


7.4 


4.1 


11.2 


6.4 


13.0 


8.2 




Range 


1.4-19.4 


0.0-12.0 


2.0-37.2 


0.0-32.2 


4.2-39.6 


1.5-36.3 



THC, A"-tetrahydrocannabinol; THC-COOH, 1 1 -carboxy-THC. 
From ref. 7. 



mL) were linked by several authors to recent use (within 6-8 hours) and consequently 
potential impairment of some psychomotor functions (8-10). Other authors have sug- 
gested that whole blood concentrations of 1.6 ng/mL or greater may cause psychomo- 
tor effects. 

Detection of THC-COOH in the absence of any detectable parent drug is a not 
infrequent finding in DUID cases. This emphasizes the importance of using appropri- 
ate cutoffs for confirmatory testing, which should be of the order of 1 ng/mL or less 
for both THC and THC-COOH. Assuming that those thresholds are observed, data 
such as those in Table 2 and in other work suggest that even following acute impairing 
doses of marijuana, concentrations of THC are likely to become undetectable within 3 
hours following use, whereas THC-COOH may persist longer. In chronic users, THC 
concentrations of 2 ng/mL have been shown to persist for more than 12 hours. 

These limitations highlight the importance of obtaining a timely blood sample 
when investigating cases of impaired driving attributed to marijuana use. 

2.1.1.2.2. THC:THC-COOH Ratio 

As noted previously, peak psychomotor and cognitive effects following mari- 
juana use occur within the first hour after smoking, a time interval during which the 
THC concentration is falling rapidly and THC-COOH is beginning to appear as a 
result of oxidative metabolism. Several studies (2,6,10) suggest that following single 
acute administration, THC-COOH concentrations will surpass THC concentrations 
within 30-45 minutes following initiation of use (see, e.g., the patterns in Table 2). 
Consequently, THC/THC-COOH ratios of greater than 1 suggest use within the prior 
hour, the period during which effects are likely to be greatest. 

In practice, in a DUI setting, the likelihood of obtaining a specimen during the 
hour following initiation of smoking is small because of the time taken to investigate, 
assess, and obtain a sample from a subject. 

Algorithms for predicting time of marijuana use based on both THC concentra- 
tions and the THC/THC-COOH ratio have been described (9,11). Although prelimi- 
nary data suggest that these models are accurate in predicting a likely time interval for 



Marijuana and Driving Impairment 



285 



Table 3 

Distribution of THC and THC-COOH Concentrations in Forensic 
Serum Specimens (n = 212) a 



Level (ng/mL) 


<0.5 


0.5-3.0 


3.0-5.0 


5.0-7.0 


7.0-9.0 


>9.0 


THC 


32% 


55% 


9% 


2% 


2% 


0.5% 


THC-COOH 


26% 


42% 


18% 


8% 


2% 


4% 



THC, A'-tetrahydrocannabinol; THC-COOH, 1 1 -carboxy-THC. 
The corresponding whole blood concentrations would be approximately 
half the reported serum amount. 
From ref. 13. 



last use following single acute moderate doses, they have not been extensively evalu- 
ated in chronic users and have not been evaluated with THC concentrations of less 
than 2 ng/mL, precluding their use in many DUID cases. Although these models may 
be informative for evaluation of cases, readers are urged to exercise caution in their 
application in a forensic setting because their limitations are still debated (12). More 
extensive evaluation of this approach in chronic users is promising and warrants fur- 
ther study. 

In a report of a gas chromatography/mass spectrometry method for the simulta- 
neous determination of THC and THC-COOH in serum (13), this method was applied 
to serial samples from subjects smoking 300 [ig of THC/kg body weight and to 212 
forensic serum specimens, including driving cases. The samples from the smoking 
study showed that THC concentrations in serum had fallen below 5 ng/mL (equivalent 
of 2.5 ng/mL in blood) in 33% of subjects within 100 minutes, and in 92% of subjects 
within 160 minutes following smoking. The distribution of concentrations of THC 
and THC-COOH in the forensic cases is shown in Table 3 and illustrates that delays 
between the time of driving and the time of sample collection can result in undetect- 
able THC concentrations. Of these cases, 87% have blood equivalent THC concentra- 
tions of less than 1.5 ng/mL. 

2.1.1.3. Toxicological Evidence: Oral Fluid (Saliva) 

Oral fluid (saliva) is receiving a lot of scrutiny for its efficacy in detecting mari- 
juana usage at the time of driving. Oral fluid is a plasma ultrafiltrate produced through 
the parotid and other glands in the mouth. Many water-soluble drugs appear in this 
ultrafiltrate and can be detected by on-site immunoassays. Because of its lipophilicity, 
THC does not readily transfer from the blood to the oral fluid, but contamination of 
the oral cavity during smoking, from the smoke and possibly from marijuana debris 
from the cigarette, can result in a positive test within 30-90 minutes of use. 

Oral fluid testing is still somewhat controversial. Many of the devices currently 
being sold are not consistently reliable, are subject to operator error, and are not com- 
prehensive in terms of the drugs they test for. Additionally, the role of roadside testing 
is still a subject of debate. Because the tests are not comprehensive, drivers who appear 
impaired should be arrested regardless of the results of the roadside test, making it 
somewhat superfluous. The presence of the drug must still be confirmed by forensi- 
cally acceptable techniques, requiring resampling or preservation of the roadside sample 
and subsequent laboratory tests. 



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2.1.1.4. Summary 

Blood concentrations of both THC and THC-COOH drop precipitously in the 
first few hours following smoking, because these substances partition into fatty com- 
partments. It is recommended that blood or plasma concentrations of THC and THC- 
COOH be interpreted with caution. Under most circumstances, detection of parent 
THC will reflect recent use, meaning within the last few hours, making the likelihood 
of impairment within that time frame that much greater. More distant, higher-intensity 
marijuana use cannot be ruled out, however, when THC is detected, and under that 
pattern of use impairment may persist longer than the 2-3 hours typical of the low- to 
moderate-dose administration. Detection of THC-COOH in the absence of the parent 
drug (i.e., <2 ng/mL) tends to suggest more distant use (>2 hours). It should go with- 
out saying that the screening threshold and confirmatory test sensitivity of the analyti- 
cal laboratory must be taken into consideration when evaluating these results. 

3. Epidemiology of Marijuana and Driving 

A thorough review of epidemiological studies related to marijuana in various 
driving populations was done recently by Huestis ( 14), and we will not attempt to repli- 
cate that in this chapter. The focus of this discussion is on studies that have attempted to 
relate marijuana use to risk of accident involvement or accident culpability. 

A survey of many of the studies cited by Huestis shows various rates of mari- 
juana positivity in impaired drivers, fatally injured drivers, drivers injured in motor 
vehicle accidents, and commercial vehicle operators. The rates of positivity vary 
depending on whether blood or urine was tested, whether the parent or metabolite was 
tested for, whether the samples were provided voluntarily or following arrest, the sen- 
sitivity of the testing method, and whether the study group was selected out (e.g., only 
subjects without alcohol tested). In spite of these variables, in the fatally injured driv- 
ing population overall, 10-20% of drivers test positive for cannabinoids, whereas in 
the arrest population rates are between 15 and 60%, suggesting a significant role for 
marijuana use. 

None of these studies has control data, however, that would show the rate of 
marijuana use in the local driving population not killed or injured in a collision, such 
that a comparative rate or odds ratio for fatal accident involvement could be calcu- 
lated. Another limiting factor was that in some studies urine was tested, and, as noted 
above, urine can test positive for marijuana use for a few days following use, while the 
impairing effects last only for a few hours. 

These studies do uniformly find evidence, however, that there is widespread use 
of marijuana in all these driving populations. In nonselected populations (e.g., all fatally 
injured drivers, trauma patients), the incidence of cannabinoid positives was typically 
between 5 and 20%, and in selected populations (e.g., young males, fatally injured 
drivers) the rate was as high as between 15 and 60%. 

A recent voluntary test of commercial vehicle operators in Washington and Oregon 
( 15) showed a marijuana-positive rate of 5%, in spite of a 19% refusal rate in what is 
a heavily regulated industry with mandatory random testing. A similar survey done in 
1988 showed 15% of tractor trailer drivers positive for cannabinoids, suggesting some 
improvement following the introduction of testing (16). 



Marijuana and Driving Impairment 



287 



3.1. Assessment of Relative Crash Risk Following Marijuana Use 

Studies that have assessed crash responsibility offer more insight into the quan- 
titative relationship between marijuana usage and crash involvement. An excellent 
review of culpability studies has recently been published (17). The general design of 
these studies is to compare rates of drug use in at-fault drivers vs no-fault drivers and 
compute the ratio, with values greater than 1.0 indicating increased rates of risk. The 
95% confidence interval is also computed, and when the range includes 1.0, the differ- 
ence in responsibility rates is not significant at the p = 0.05 level. 

In most of these studies, authors validate their data set and methodology by 
assessing odds ratios for alcohol. The relationship between alcohol and risk of crash 
involvement has been well established, most famously in the 1960 Grand Rapids Study. 
In each case the method showed the expected significant relationship at the p = 0.05 
(95% confidence interval) level between alcohol positivity and greater odds of crash 
involvement. 

The data from studies that made odds ratio assessments based on the presence of 
the inactive THC-COOH metabolite uniformly failed to show significant differences 
at the p = 0.05 level in rates of accident involvement for the drug-positive drivers. 
This can be rationalized in terms of the fact that the metabolite is inactive and that in 
most cases urine was being tested. Bearing this in mind, together with the fact that 
urine can test positive for the metabolite for many hours or even days after the effect 
has passed, its detection in urine is not a good surrogate for impairment, and the nega- 
tive findings are not surprising. 

Studies assessing crash risk based on parent THC in blood are more informative. 
One study of 2500 injured drivers (18,19) showed a trend towards increasing odds 
ratio with increasing THC concentration (although not significant at p = 0.05) and 
found that culpable drivers had a higher mean THC concentration (p = 0.057). This 
suggests a dose-dependent increase in risk, with the threshold for significance being 
somewhere above 2 ng/mL THC. One limitation of the Hunter study is the lack of 
control of the interval between driving and when the sample was collected. Intervals 
of an hour or less between the driving and the time the sample was collected would 
cause appreciable decreases in THC concentration. 

In a cohort of 3398 fatally injured drivers (20), the authors avoid this limitation 
because absorption of THC will stop at the time of death. Those data showed an odds 
ratio of 2.7 in cases in which THC was detected and 6.6 when the THC concentration 
was greater than 5 ng/mL. 

Several studies have evaluated crash risk in drivers positive for both alcohol and 
marijuana (THC or THC-COOH). Table 4 shows that irrespective of whether the par- 
ent drug or metabolite was measured, when combined with alcohol the odds ratio for 
crash involvement was between 3.5 and 11.5 (significant in all cases, p = 0.05) and 
compared to alcohol positive cases was still significant, with an odds ratio of 2.9. 

Taken together, these data represent strong evidence for a concentration-de- 
pendent (and consequently dose-dependent) relationship between THC and risk of 
crash involvement and enhanced risk for any use of marijuana when combined 
with alcohol. 



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Table 4 

Summary of Odds Ratio of Becoming Involved in Fatal or Injurious Traffic 
Accidents Under the Influence of Cannabis, Alcohol, or Their Combination as 
Reported in Culpability Studies 



Substance 


Authors 


Odds ratio 


95% CI 


Drug-free cases 




1.0 




Alcohol 


Terhune and Fell (21) 


5.4* 


2.8-10.5 




Williams et al. (22) 


5.0* 


2.1-12.2 




Terhune et al. (23) 


5.7* 


5.1-10.7 




Drummer (24) 


5.5* 


3.2-9.6 




Hunter et al. (18) 


6.8* 


4.3-11.1 




Lowenstein and Koziol-Mclain (25) 


3.2* 


1.1-9.4 




Drummer et al. (20) 


6.0* 


4.0-9.1 


THC-COOH 


Terhune and Fell (21) 


2.1 


0.7-6.6 




Williams et al. (22) 


0.2 


0.2-1.5 




Terhune et al. (23) 




9 8 




Drummer (24) 


0.7 


0.4-1.5 




Hunter et al. (18) 


0.9 


0.6-1.4 




Lowenstein and Koziol-Mclain (25) 


1.1 


0.5-2.4 


TCH (range: ng/mL) 






<1.0 


Hunter et al. (18) 


0.35 


0.02-2.1 


1.10-2.0 




0.51 


0.2-1.4 


>2.0 




1.74 


0.6-5.7 


1-100 


Drummer et al. (26) 


2.7* 


1.02-7.0 


5-100 




6.6* 


1.5-28.0 


Alcohol/THC or 


Williams et al. (22) 


8.6* 


3.1-26.9 


THC-COOH 


Terhune et al. (23) 


8.4* 


2.1-72.1 




Drummer (24) 


5.3* 


1.9-20.3 




Hunter et al. (18) 


11.5* 


4.6-36.7 




Lowenstein and Koziol-Mclain (25) 


3.5* 


1.2-11.4 


Significant chanj 
THC-COOH, 1 1 
From ref. / /. 


*es in OR indicated as follows: *<0.05. 
-carboxy-THC; THC, A 9 -tetrahydrocannabino 


1. 





4. Marijuana and On-Road Driving Studies 

The above considerations suggest that in addition to the empirical intoxicating 
properties of marijuana, there is epidemiological and behavioral evidence that it can 
cause impairment in the first few hours following use. Assessments of psychomotor 
performance following marijuana use have been performed, and these have been 
reviewed recently by Ramaekers et al. (17). These studies support the idea that dose- 
dependent impairments in psychomotor performance and cognition appear immedi- 
ately following marijuana administration, peak after the blood concentration peaks, 
and persist for 3-4 hours. Although there is a relationship between many of these 
tasks and the driving task, the clearest means of assessing the actual effects of mari- 



Marijuana and Driving Impairment 



289 



juana on drivers is to measure their performance in actual on-road driving following 
marijuana administration. A number of such studies have been done. 

4.1. Study of Klonoff et al. (27) 

Conducted in Vancouver, British Columbia, in the early 1970s, drivers were dosed 
with 4.9 or 8.4 mg of THC by smoking. This represents 70 and 120 fig/kg, respec- 
tively, in a 70-kg person, compared with the 300 M-g/kg described by Robbe and 
O'Hanlon (7) as the user-preferred dose, so both should be considered relatively low- 
dose conditions compared to normal patterns of use. Following drug administration, 
drivers drove both on a closed traffic free course and on the streets of downtown 
Vancouver during peak traffic hours. Driving performance was rated subjectively by a 
professional driving examiner. Researchers found subtle differences between the mari- 
juana and placebo conditions and noted some bidirectional changes in performance. 
Sixty-four volunteers drove the driving course. There was a trend towards a greater 
number of subjects, demonstrating poorer performance going from placebo to low 
dose to high dose, with 73% of the high-dose subjects demonstrating a decline in 
performance. However, 23% of subjects demonstrated an increase in performance in 
the high-dose condition, with 14% showing significant improvement. 

Thirty-eight subjects participated in the on-street driving. Similarly, although 
79% of subjects demonstrated a decline in driving performance, 16% demonstrated 
improved performance even in the high-dose condition. 

The components of driving that were most affected by marijuana following the 
high dose were judgment, care while driving, and concentration. Minimally affected 
were factors such as general driving ability, speed, confidence, and aggression, and 
cooperation and attitude were unaffected. Unusual behaviors documented in drivers 
after marijuana use included missing traffic lights or stop signs, passing without suffi- 
cient caution, poor anticipation or handling of the vehicle with respect to traffic flow, 
inappropriate awareness of pedestrians or stationary vehicles, and preoccupation and 
lack of response at green lights. 

Although the tendency was toward deterioration in driving performance with 
increasing dose of marijuana, the trend was not uniform. The authors struggled to 
explain the bidirectional changes in performance and hypothesize that interindividual 
differences in response can outweigh dose-related effects, and that subjects can recog- 
nize impairment and compensate, and in some cases overcompensate, resulting in 
improvement. 

Caution should be exercised in applying the results of this study to users engag- 
ing in more demanding driving and also to drivers using higher doses and more potent 
marijuana. 

4.2. Study of Robbe and O'Hanlon (7) 

The most comprehensive work on marijuana in actual on-road driving has been 
done at the University of Maastricht in the Netherlands, beginning with this report. 
The authors first made an assessment of the dose of marijuana preferred by users, so 
that appropriate doses could the assessed for their effects on driving. Twenty-four 
subjects who used the drug more than once a month and less than daily and who had 
driven within an hour of marijuana use within the last year were assessed. Their aver- 



290 



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age preferred dose to achieve the desired psychological effect was 20.8 mg, which 
after adjustment for body weight was 308 M-g/kg, with no significant difference for 
males and females. 

Subjects were tested on a closed driving course with doses of 0, 100, 200, and 
300 M-g/kg THC. Interestingly, 40-60% of the subjects indicated that they would have 
been willing to drive for unimportant reasons shortly after smoking the two highest 
doses. Driver performance was assessed by measurement of standard deviation of lat- 
eral position (SDLP), an index of weaving that has been validated for alcohol and 
other drugs as a measurement of deterioration of driving performance. 

There was dose-dependent deterioration in SDLP. Driving performance decre- 
ment persisted undiminished for 2 hours following drug administration, even after 
perceived "high" and heart rate had declined. It also persisted even as measured plasma 
THC concentrations fell, but SDLP was not quantitatively related to plasma THC or 
THC-COOH concentrations. Drivers accurately assessed their performance as being 
poorer than normal under the two highest-dose conditions. Quantitatively, the decrement 
in SDLP was equivalent to blood alcohol concentrations (BACs) of 0.03-0.07 g/100 mL. 

Having determined the scale of the performance decrement, the researchers 
decided it was safe to evaluate driving performance on open highways around other 
vehicles under the same dosing conditions. Subjects were again dosed with 0, 100, 
200, and 300 M-g/kg THC. SDLP as an index of weaving and a car-following test where 
the subjects had to maintain headway with a lead vehicle were conducted. This phase 
confirmed the dose-dependent deterioration in SDLP, with the lower doses producing 
impairment less than 0.05 g/100 mL and the highest dose producing impairment mar- 
ginally above that. The subjects rated their performance as worse than normal at the 
two highest doses, but still expressed a willingness to drive. 

The final phase of the study involved more demanding urban city driving, and 
consequently only the placebo and lowest dose were administered because the prior 
two phases had shown significant impairment in the two highest-dose conditions. In 
this phase the driver's performance was compared against other drivers dosed to a 
0.05 g/100 mL BAC. The alcohol condition produced the expected deterioration in 
driving performance, but the 100 M-g/kg THC dose produced no measurable decline in 
urban city driving performance. Interestingly, the alcohol-impaired drivers reported 
no perceived deterioration in performance even while it was evident to the observers, 
whereas the subjects receiving the low-dose THC reported feeling impaired even while 
no impairment could be measured. This echoes the experience of Klonoff's study that 
users were compensating and often overcompensating for their perceived impairment. 

Most importantly, this careful work demonstrates that although marijuana has 
the ability to impair under certain conditions, and does so in a dose-dependent man- 
ner, the degree of impairment associated with a user-preferred dose of 300 Mg/kg pro- 
duced impairment equivalent to BACs of 0.03-0.07 g/100 mL. Additionally, it 
confirmed the lack of correlation between plasma THC concentrations and the level of 
impairment. 

4.3. Study ofLamers and Ramaekers (28) 

In this study, performed at the same institute and using the same methodology, 
researchers assessed the combined effects of alcohol and marijuana using 0.04 g/100 



Marijuana and Driving Impairment 



291 



mL BAC and 100 M-g/kg THC on urban city driving. Additionally, using a head-mounted 
eye movement-recording system, the subjects' visual search or side glances were as- 
sessed. 

This study confirmed that low doses of marijuana, or alcohol at the 0.04 g/100 
mL concentration, when taken alone, did not impair city driving or performance or 
interfere with visual search frequency at intersections. When alcohol and THC were 
taken in combination, however, visual search frequency decreased by about 3%. The 
study also confirmed the finding of previous work that subjects did not feel impaired 
when using alcohol, even when impairment was present, but did feel impaired after 
marijuana use even when no impairment was measurable. The subjects' ability to rec- 
ognize their impairment from marijuana was abolished, however, when it was con- 
sumed in conjunction with alcohol. 

5. Conclusions 

The material reviewed in this chapter highlights the challenges of assessing driv- 
ing impairment caused by marijuana. Epidemiologically, there is evidence for dose- 
dependent increases in crash risk with increasing blood THC concentration. There is 
good evidence that the prevalence of cannabinoids in the system of injured, killed, and 
arrested drivers is higher than the incidence in the population at large. Empirically, 
the drug produces effects on cognition and psychomotor performance, which have the 
potential to impair driving ability, and users recognize the presence of that impair- 
ment and can even compensate accordingly. There is good evidence that there is a 
significant dose-response relationship between marijuana use and the degree of 
impairing effects. On the other hand, the passage of time between driving or involve- 
ment in a crash limits our ability to get an accurate measurement of the THC concen- 
tration at the time of driving. More complex tasks are more sensitive to the effects of 
marijuana and increase the likelihood that that the impairment will become significant 
and observable. 

Studies of driving behavior have been conducted with typical user-preferred doses 
and show that the effects, at least on the alcohol-impairment scale, are mild to moder- 
ate and are affected by the dose, the time since use, the users' perception of the effect, 
and their degree of compensation or overcompensation for those effects. 

In short, the assessment of the role of marijuana use in a crash or impaired driv- 
ing case must be made with caution and will be most defensible when all available 
information is considered, including the pattern of driving, recent drug use history or 
admission to marijuana use, an appearance of impairment, performance in field sobri- 
ety tests, the presence of physiological signs and symptoms of marijuana use, and 
toxicological test results of blood or serum samples. 

6. General Readings 

1 . Couper, F. J. and Logan, B . K. (2004) Drugs and Human Performance Fact Sheets. NHTS A 
DOT HS 809 725. 

2. Drugs and Drug Abuse (2002) Addiction Research Foundation, Toronto. 

3. Huestis, M. A. (2002) Cannabis (marijuana) — effects on human performance and behav- 
ior. Forensic Sci. Rev. 14, 15-59. 



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References 

1. Papafotiou, K., Carter, J. D., and Stough, C. (2004) An evaluation of the sensitivity of the 
Standardised Field Sobriety Tests (SFSTs) to detect impairment due to marijuana intoxica- 
tion. Psychopharmacology (Berl). Dec 24 (published online). 

2. Huestis, M. A., Mitchell, J. M., and Cone, E. J. (1996) Urinary excretion profiles of 11- 
nor-9-carboxy-delta 9-tetrahydrocannabinol in humans after single smoked doses of mari- 
juana. J. Anal. Toxicol. 20, 441-452. 

3. Huestis, M. A., Mitchell, J. M., and Cone, E. J. (1995) Detection times of marijuana me- 
tabolites in urine by immunoassay and GC-MS. J. Anal. Toxicol. 19, 443-449. 

4. Ellis, G. M. Jr, Mann, M. A., Judson, B. A., Schramm, N. T., and Tashchian, A. (1985) 
Excretion patterns of cannabinoid metabolites after last use in a group of chronic users. 
Clin. Pharmacol. Ther. 38, 572-578. 

5. Owens, S.M., McBay, A.J., Reisner, H.M., and Perez-Reyes, M. (1981) 1251 radioimmu- 
noassay of delta-9-tetrahydrocannabinolin blood and plasma with a solid-phase second- 
antibodyseparation method. Clin. Chem. 27, 619. 

6. Skopp, G., Potsch, L., Mauden, M., and Richter, B. (2002) Partition coefficient, blood to 
plasma ratio, protein binding and short-term stability of 1 l-nor-delta(9)-carboxy tetrahy- 
drocannabinol glucuronide. Forensic Sci. Int. 126, 17-23. 

7. Robbe, H. W. and O'Hanlon, J. F. (1993) Marijuana and Actual Driving Performance. 
DOT HS 808 078. US Department of Transportation, National Highway Traffic Safety 
Administration. 

8. Barnett, G. and Willette, R. E. (1989) Feasibility of chemical testing for drug impaired 
performance, in Advances in Analytical Toxicology, (Baselt, R.C., ed.), Yearbook Medical 
Publishers, Chicago, IL, p. 218. 

9. Huestis, M. A., Henningfield, J. E., and Cone, E. J. (1992) Blood cannabinoids. II. Models 
for the prediction of time of marijuana exposure from plasma concentrations of delta 9- 
tetrahydrocannabinol (THC) and 1 l-nor-9-carboxy-delta 9-tetrahydrocannabinol 
(THCCOOH) /. Anal Toxicol. 16, 283-290. 

10. Mason, A. P. and McBay, A. J. (1985) Cannabis; Pharmacology and interpretation of ef- 
fects. J. Forensic Sci. 30, 615-631. 

11. Peat, M. A. (1989) Distribution of delta-9-tetrahydrocannabinol and its metabolites, in 
Advances in Analytical Toxicology II (Baselt, R. C, ed.), Book Medical Publishers, Chi- 
cago, IL, pp. 186-217. 

12. Bogusz, M. (1993) Concerning blood cannabinoids and the effect of residual THCCOOH 
on calculated exposure time. J. Anal. Toxicol. 17, 313-316. 

13. Moeller, M. R., Doerr, G., and Warth, S. (1992) Simultaneous quantitation of delta-9- 
tetrahydrocannabinol (THC) and 1 l-nor-9-carboxy-delta-9-tetrahydrocannabinol (THC- 
COOH) in serum by GC/MS using deuterated internal standards and its application to a 
smoking study and forensic cases. /. Forensic Sci. 37, 969-983. 

14. Huestis, M.A. (2002) Cannabis (marijuana) — effects on human performance and behavior. 
Forensic Sci. Rev. 14, 15-59. 

15. Couper, F. J., Pemberton, M., Jarvis, A., Hughes, M., and Logan, B. K. (2002) Prevalence 
of drug use in commercial tractor-trailer drivers. J. Forensic Sci. 47, 562-567. 

16. Lund, A. K., Preusser, D. F., Blomberg, R. D., and Williams, A. F. (1988) Drug use by 
tractor-trailer drivers. /. Forensic Sci. 33, 648-661. 

17. Ramaekers, J. G., Berghaus, G., van Laar, M., and Drummer, O. H. (2004) Dose related 
risk of motor vehicle crashes after cannabis use. Drug Alcohol Depend. 73, 109-1 19. 

18. Hunter, C. E., Lokan, R. J., and Longo, M. C. (1998) The prevalence and role of alcohol, 
cannabinoids, benzodiazepines and stimulants in non-fatal crashes. Forensic Science, De- 
partment for Administrative and Information Services, Adelaide, South Australia. 



Marijuana and Driving Impairment 



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19. Longo, M. C, Hunter, C. E., Lokan, R. J., White, J. M., and White, M. A. (2000) The 
prevalence of alcohol, cannabinoids, benzodiazepines and stimulants amongst injured driv- 
ers and their role in driver culpability: part II: the relationship between drug prevalence 
and drug concentration, and driver culpability. Accid. Anal. Prev. 32, 623-632. 

20. Drummer, O. H., Gerostamoulos, J., Batziris, H., et al. (2004) The involvement of drugs in 
drivers of motor vehicles killed in Australian road traffic crashes. Accid. Anal. Prev. 36, 
239-248. 

21. Terhune, K. W. and Fell, J.C. (1982) The role of alcohol, marijuana and other drugs in the 
accidents of injured drivers. (Tech. Rep. under Contract No. DOT-HS-5-01 179). Calspan 
Field Services Inc., Buffalo, NY. 

22. Williams, A. F., Peat, M. A., Crouch, D. J., Wells, J. K., and Finkle, B. S. (1985) Drugs in 
fatally injured young male drivers. Public Health Rep. 100, 19-25. 

23. Terhune, K. W., Ippolito, C. A., Hendriks, D. L., and Michalovic, J. G. (1992) The inci- 
dence and role of drugs in fatally injured drivers. National Highway Traffic Safety Admin- 
istration, Final Report under Contract No. DTNH 22-88-C-07069. 

24. Drummer, O. H. (1994) Drugs in drivers killed in Australian road traffic accidents. Victo- 
rian Institute of Forensic Pathology, Institute of Forensic Medicine, Monash University, 
Melbourne, Australia (report no. 0594). 

25. Lowenstein, S. R. and Koziol-Mclain, J. (2001) Drugs and traffic crash responsibility: a 
study of injured motorists in Colorado. J. Trauma 50, 313-320. 

26. Drummer, O. H., Gerostamoulos, J., Batziris, H., et al. (2003) The incidence of drugs in 
drivers killed in Australian road traffic crashes. Forensic. Sci. Int. 134, 154-162. 

27. Klonoff, H. (1974) Marijuana and driving in real-life situations. Science 186, 317-324. 

28. Lamers, C. T. and Ramaekers, J. G. (2001) Visual search and urban driving under the 
influence of marijuana and alcohol. Hum. Psychopharmacol. 16, 393-401. 



Chapter 13 



Postmortem Considerations 



Steven B. Karch 

1. Introduction 

The prevalence of marijuana smoking among adults in the United States has 
remained stable, at approx 4%, for the last decade (I). Even that low rate (four times 
as many Americans smoke cigarettes) still translates into more than 6 million active 
users. In 2002, an estimated 19.5 million Americans aged 12 years or older admitted 
to having used illicit drugs during the month before the survey interview, and that 
number translates into 8.3% of the population over the age of 12 (Fig. 1). Of these 
individuals, 75% reported using marijuana, and 72 million individuals report having 
smoked marijuana at least once in their life (2). Given the surprisingly large number 
of users, it is quite surprising to see how little has been written about marijuana toxic- 
ity. Reports of acute life-threatening illness, or at least reports emanating from the 
offices of medical examiners, are extraordinarily rare. 

There is, however, no doubt that marijuana smoking does have measurable car- 
diovascular effects, and cardiovascular disease is the principal cause of death in the 
United States. (Surprisingly, cardiovascular disease is the third leading cause of death 
for children under age 15 [3], accounting for at least one in five deaths [approx 2500 
deaths per day].) Coronary heart disease alone is the single largest killer of Ameri- 
cans, and stroke is the third. Each year, about 700,000 people experience a new or 
recurrent stroke. About 500,000 of these are first attacks, and 200,000 are recurrent. 
Stroke accounted for more than one of every 15 deaths in the country in 2001. In total, 
cardiovascular disease killed 931,108 Americans in 2001 (compared with 553,768 
deaths from cancer, 101,537 accidental deaths, 53,852 deaths from Alzheimer's dis- 
ease, and 14,175 from HIV). 

Because the number of marijuana smokers is very large, it is inevitable that there 
would be overlap between the two groups. The difficulty for pathologists is deciding 

From: Forensic Science and Medicine: Marijuana and the Cannabinoids 
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey 

295 



296 



Karch 



Marijuana and 
Some Other 
/ Drug 



Marijuana 
Only 




Only Drug 
Other than 
Marijuana 



Fig. 1. Current breakdown of illicit drug use in the United States. 

when an individual with cardiovascular disease has died "from" their marijuana smoking 
or "with" marijuana smoking. Currently available diagnostic techniques do not permit 
making such distinctions. This chapter reviews what is known about the cardiovascu- 
lar consequences of marijuana smoking, with special emphasis on marijuana as a trig- 
gering factor for plaque rupture and sudden cardiac death. Evidence for other 
marijuana-related illnesses and medical effects will be reviewed, as will postmortem 
testing methodologies. 

2. Pharmacokinetics and Pharmacodynamics 

A brief overview of aspects relevant to death investigation is provided here. A 9 - 
Tetrahydrocannabinol (THC) is highly lipophilic and essentially water insoluble (4). 
It is destroyed by exposure to heat and is also photolaible (5). These physical proper- 
ties have considerable relevance to the storage and testing of postmortem specimens. 
It has never been proven that overdose has caused the death of humans, dogs (in oral 
doses of up to 3000 mg/kg), or monkeys (in oral doses up to 9000 mg/kg; ref. 6). 

Most (>90%) THC is distributed to the plasma, with 10% in red blood cells (7). 
Almost all of the THC in plasma is protein bound, mainly to lipoproteins, but also to 
albumin (8). These physical properties must be considered when making postmortem 
measurements; postmortem measurements are conducted on whole blood, but the phar- 
macokinetic data sometimes used to interpret these concentrations are based on mea- 
surements made using plasma obtained from the living. 

THC is extremely lipophilic, but, because of strong protein binding, it has a rela- 
tively small apparent plasma volume of 2-4 L, at least initially (9). The steady-state 
volume of distribution is much higher (10 L/kg; ref. 10). Plasma THC levels decline 
very rapidly because tissue uptake is so rapid. Only small amounts (probably <\%) 
reside in the brain during periods of peak psychoactivity (11). This seemingly para- 
doxical finding is explained by the brain's very high blood flow and the ease with 
which THC enters and departs cells ( 12). With repeated use, THC accumulates in less 



Postmortem Considerations 



297 



vascular tissue, especially body fat (13). This property makes fat a useful alternative 
matrix for testing (14). 

Maximum plasma concentrations occur within minutes of smoking, and psycho- 
logical effects become apparent within a few seconds to a few minutes. Maximum 
psychological effects are observed after 15-30 minutes, and these taper off within 2- 
3 hours. When taken orally there is a delay of 30-90 minutes before the onset of 
psychotropic effects, and these effects remain relatively constant for 2-3 hours. The 
psychological effects then dissipate slowly over the following 4-12 hours (15). 

3. Cardiovascular Effects 

THC, the major psychoactive component of Cannabis sativa, like anandamide, the 
endogenous cannabinoid ligand, activates G protein-coupled receptors in the heart, brain, 
and periphery. Two distinct types of cannabinoid receptors have been identified: CB, 
and CB 2 . Activation of peripheral CB, receptors elicits profound coronary and cerebral 
vasodilatation (16). In vitro studies have shown that this response is a result of direct 
receptor activation and that the process occurs independently of the sympathetic ner- 
vous system (17). In animal models, the predictable result is hypotension. 

In humans the vascular response is a largely dose-dependent increase in heart 
rate, usually accompanied by a mild increase in systolic pressure, although orthostatic 
hypotension is a recognized complication in occasional users. Studies with human 
volunteers have shown that complete tolerance to the tachycardiac and blood pressure 
effects develops and that electrocardiographic alterations produced by marijuana smok- 
ing are minimal (18). 

Whether or not these recognized cardiovascular effects are sufficient to actually 
trigger myocardial infarction is still debated, although there is ample evidence for 
concern. The acute onset of coronary syndromes is thought to result from the disrup- 
tion of vulnerable plaque. Vulnerable plaques are not necessarily the largest plaques 
(i.e., they do not cause clinically significant obstruction of large epicardial arteries) 
but, rather, are comprised of thin-capped, lipid-rich lesions that may be located in 
second-order vessels. "Triggers," whether intense athletic activity, marijuana smok- 
ing, or even intense sexual activity, result in homodynamic forces that can disrupt the 
thin fibrous cap, probably because changes in arterial pressure disrupt the underlying 
vulnerable plaque (19). 

Epidemiological evidence supports the triggering theory. Investigators in the 
Myocardial Infarction Onset Study interviewed 3882 patients (1258 women) hospital- 
ized with acute myocardial infarction (20). Of these, 124 (3.2%) reported smoking 
marijuana in the prior year, 37 within 24 hours and 9 within 1 hour of the onset of 
symptoms. As is true for most patients with coronary artery disease, marijuana users 
were more likely to be men (94 vs 67%, p < 0.001), more likely to be current cigarette 
smokers (68 vs 32%, p < 0.001), and more likely to be obese (43 vs 32%, p = 0.008). 
The risk of myocardial infarction onset in the marijuana smokers was elevated 4.8 
times over baseline (95% confidence interval 2.4-9.5) in the 60 minutes after mari- 
juana use, dropping to a relative risk of 1 .7 in the second hour, after which no increase 
risk was apparent. 



298 



Karch 



The authors of the study concluded that smoking marijuana was a rare trigger of 
acute myocardial infarction. A number of other "triggers" for myocardial infarction 
have been identified (21,22). These include heavy physical exertion, mental stress, 
particulate air pollution, and sexual activity. The increased relative risk associated 
with sexual activity is comparable to that associated with marijuana smoking — roughly 
double the relative risk of acute myocardial infarction in healthy individuals or even 
in patients with a prior history of angina or those with prior infarction. 

Although the relative risk for infarction is definitely increased, the absolute risk 
of marijuana-triggered infarction is extremely low because the baseline risk of infarc- 
tion is low for most individuals. The increased risk is transient, probably because 
marijuana-induced changes in pulse and blood pressure changes are transient, if they 
occur at all. Tolerance to vascular effects rapidly emerges in chronic marijuana smok- 
ers. These factors must be given due weight in any cause of death determination. 

4. Other Medical Effects 

Chronic marijuana smoking is clearly related to lung injury, although there is 
nothing diagnostic about the resultant pattern of injury (23). Because of the way mari- 
juana is smoked, more particulate matter is generated than by smoking tobacco, which 
means that damage to the respiratory tract is more likely than with tobacco smoking. 
The effects of cannabis and tobacco smoking are additive and independent. The resultant 
histopathological effects include changes consistent with acute and chronic bronchitis 
but are in no way diagnostic. In the only published autopsy series, lungs were exam- 
ined in 13 known marijuana smokers with sudden death. Decedents ranged in age 
from 15 to 40 years. There were accumulations of pigmented monocytes within 
the alveoli and variable, spotty, infiltrates of monocytes and lymphocytes within the 
intersititum. The study authors suggest that the degree of infiltrate was dose-related, 
with heavier smokers having heavier infiltrates (24). 

Alveolar macrophages recovered from the lungs of marijuana smokers have a 
decreased ability to release pro-inflammatory cytokines and nitric oxide and are less 
effective at killing bacteria. THC alters human immune responses. Lymphocytes of 
marijuana smokers contain increased amounts of messenger RNA encoding for both 
type 1 and 2 cannabinoid receptors. THC suppresses T-cell proliferation, inhibits the 
release of interferon-y, and alters the production of T-helper cytokines (25). Habitual 
exposure to THC impacts human cell-mediated immunity and host defenses, but there 
is little evidence to support the notion that, like tobacco smoking, cannabis exposure 
actually causes malignancy. In fact, there is equally good evidence that, as a group, 
cannabinoids induce tumor regression in rodents. The mechanism of cannabinoid an- 
titumoral action in vivo is as yet unknown, but it may involve the direct inhibition of 
vascular endothelial cell migration and survival as well as decreased expression of 
pro- angiogenic factors (vascular endothelial growth factor and angiopoietin-2) and 
matrix metalloproteinase-2 found within tumors. 

5. Postmortem Measurements 

Forensic pathologists occasionally screen for THC and its metabolites, but only 
if impairment is an issue or, in the rare episode of atherosclerotic sudden cardiac death, 



Postmortem Considerations 



299 



where "trigger" factors are being sought. Routine screening for cannabanoids is, how- 
ever, not considered cost-effective (an important issue for medical examiner's offices). 
When nonspecific populations have been screened, results have generally mirrored 
patterns of drug abuse within the rest of the population. Of 500 sequential specimens 
screened by the Medical Examiner's Office in Maryland, 63 (13%) were initially posi- 
tive by enzyme multiplied immunoassay technique, and 58 of those (12%) were con- 
firmed positive (26). 

6. Cause-of-Death Determination 

There are no unique or diagnostic lesions associated with acute THC toxicity. It 
is not even clear what the clinical signs of massive overdose would be. Pathological 
abnormalities identified in chronic users are likely to be a consequence of chronic 
polydrug abuse and are nonspecific. The question to be answered by forensic patholo- 
gists is whether marijuana use has "triggered" an episode of myocardial infarction or 
sudden cardiac death, but answers are unlikely to be forthcoming. "Trigger" theories 
can only be applied in situations in which coronary artery disease is already estab- 
lished, which almost surely means that the decedent will be in an older age group, the 
very group most likely to experience myocardial infarction in the first place. 

Blood and tissue measurements of THC are of little or no diagnostic value in 
cause-of-death determination and are seldom measured. Even when postmortem blood 
concentrations are measured, a number of toxicological issues make interpretation of 
these measurements difficult. Perhaps the greatest impediment to interpretation is that 
all published studies (and formulas for predicting time of use) are based on measure- 
ment made in plasma (27,28). Even in the living, relating measurement made in whole 
blood to measurements made in plasma is problematic. When THC, 1 1-OH-THC, and 
THC-COOH concentrations were measured in the plasma and whole blood taken from 
eight chronic marijuana smokers, the values of the plasma-to-whole blood distribu- 
tion ratios were very similar, and the individual coefficient of variation was relatively 
low. These results suggest that plasma levels could be calculated from whole blood 
concentrations by taking into account a multiplying factor of 1.6. Unfortunately, simi- 
lar attempts with postmortem "blood" resulted in a distribution of cannabinoids be- 
tween whole blood and "serum" that was scattered over too wide a range to be of any 
forensic value; the Huestis models could not be applied (29). 

Tolerance to the vascular — and many of the psychological — effects of marijuana 
smoking rapidly emerges, and even in the living, plasma concentrations do not predict 
pulse or blood pressure (18). Slow diffusion of THC from plasma into body fat and 
reentry into the blood is a constant ongoing process. Within 6-8 hours after use, plasma 
THC concentrations drop below 2 |J.g/L, and then continue to decrease somewhat more 
slowly. After smoking cigarettes containing 16 mg (low dose), levels fall below 0.5 [ig/L 
(the limit of detection for most laboratories) after 7.2 hours (27,28). When the dose is 
doubled, plasma concentration remained above 0.5 for an average of 12.5 hours, and 
THC-COOH remained detectable for an average of 3.5 days. 

With higher doses and long-term use, substantial amounts of THC and its 
metabolites accumulate in deep body stores (30). After death these stores are slowly 
released. Although there exist a host of reliable methods for THC extraction (31) and 



300 



Karch 



quantitation (32), THC's large volume of distribution virtually guarantees that post- 
mortem redistribution will occur, which means that postmortem THC concentration 
measurements are of even less use than antemortem measurements, which is to say 
not at all. 

References 

1. Compton, W. M., Grant, B. F., Collier, J. D., Glantz, M. D., and Stinson, F. S. (2004) 
Prevalence of marijuana use disorders in the United States: 1991-1992 and 2001-2002. 
JAMA 291, 2114-2121. 

2. Substance Abuse and Mental Health Service Administration. (2003) Results: 2002 Na- 
tional Survey on Drug Use & Health (NSDUH), in NHSDA Series H-22, DHHS Publica- 
tion NO SMA 03-3836, O.o.A. Studies, Rockville, MD. 

3. American Heart (2004) American Heart Association's Heart Disease and Stroke Statis- 
tics— 2004 Update, in Stats2004, NR03, Dallas. 

4. Garrett, E. R. and Hunt, C. A. (1974) Physiochemical properties, solubility, and protein 
binding of delta9-tetrahydrocannabinol. J. Pharm. Sci. 63, 1056-1064. 

5. Agurell, S. and Leander, K. (1971) Metabolism of cannabis. VIII. Stability, transfer and 
absorption of cannabinoid constituents of cannabis (hashish) during smoking. Acta Pharm. 
Suec. 8, 391-402. 

6. Thompson, G. R., Rosenkrantz, H, Schaeppi, U. H, and Braude, M. C. (1973) Compari- 
son of acute oral toxicity of cannabinoids in rats, dogs and monkeys. Toxicol. Appl. 
Pharmacol. 25, 363-372. 

7. Widman, M., Agurell, S., Ehrnebo, M., and Jones, G. (1974) Binding of (+)- and (minus)- 
delta-1 -tetrahydrocannabinols and (minus)-7-hydroxy-delta-l -tetrahydrocannabinol to 
blood cells and plasma proteins in man. /. Pharm. Pharmacol. 26, 914-916. 

8. Wahlqvist, M., Nilsson, I. M., Sandberg, F., and Agurell, S. (1970) Binding of delta-1- 
tetrahydrocannabinol to human plasma proteins. Biochem. Pharmacol. 19, 2579-2584. 

9. Wall, M. E., Sadler, B. M., Brine, D., Taylor, H, and Perez-Reyes, M. (1983) Metabolism, 
disposition, and kinetics of delta-9-tetrahydrocannabinol in men and women. Clin. 
Pharmacol. Ther. 34, 352-363. 

10. Lemberger, L., Tamarkin, N. R., Axelrod, J., and Kopin, I. J. (1971) Delta-9-tetrahydro- 
cannabinol: metabolism and disposition in long-term marihuana smokers. Science 173, 
72-74. 

11. Gill, E. W. and Jones, G. (1972) Brain levels of deltal-tetrahydrocannabinol and its me- 
tabolites in mice — correlation with behaviour, and the effect of the metabolic inhibitors 
SKF 525A and piperonyl butoxide. Biochem. Pharmacol. 21, 2237-2248. 

12. Chiang, C. N. and Rapaka, R. S. (1987) Pharmacokinetics and disposition of cannabinoids. 
NIDA Res. Monogr. 79, 173-188. 

13. Kreuz, D. S. and Axelrod, J. (1973) Delta-9-tetrahydrocannabinol: localization in body fat. 
Science 179, 391-393. 

14. Levisky, J. A., Bowerman, D. L., Jenkins, W. W., Johnson, D.G., and Karch, S. B. (2001) 
Drugs in postmortem adipose tissues: evidence of antemortem deposition. Forensic Sci. 
Int. 121, 157-160. 

15. Grotenhermen, F. (2003) Pharmacokinetics and pharmacodynamics of cannabinoids. Clin. 
Pharmacokinet. 42, 327-360. 

16. Wagner, J. A., Jarai, Z., Batkai, S., and Kunos, G. (2001) Hemodynamic effects of cannab- 
inoids: coronary and cerebral vasodilation mediated by cannabinoid CB 1 receptors. Eur. J. 
Pharmacol. 423, 203-210. 

17. Sidney, S. (2002) Cardiovascular consequences of marijuana use. /. Clin. Pharmacol. 
42(11 Suppl.), 64S-70S. 



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18. Benowitz, N. L. and Jones, R. T. (1975) Cardiovascular effects of prolonged delta-9-tet- 
rahydrocannabinol ingestion. Clin. Pharmacol. Ther. 18, 287-297. 

19. Servoss, S. J., Januzzi, J. L., and Muller, J. E. (2002) Triggers of acute coronary syn- 
dromes. Prog. Cardiovasc. Dis. 44, 369-380. 

20. Mittleman, M. A., Lewis, R. A., Maclure, M., Sherwood, J. B., and Muller, J. E. (2001) 
Triggering myocardial infarction by marijuana. Circulation 103, 2805-2809. 

21. Mittleman, M. A., Maclure, M., Nachnani, M., Sherwood, J. B., and Muller, J.E. (1997) 
Educational attainment, anger, and the risk of triggering myocardial infarction onset. The 
Determinants of Myocardial Infarction Onset Study Investigators. Arch. Intern. Med. 157, 
769-775. 

22. Mittleman, M. A. and Siscovick, D. S. (1996) Physical exertion as a trigger of myocardial 
infarction and sudden cardiac death. Cardiol. Clin. 14, 263-270. 

23. Barsky, S. H., Roth, M. D., Kleerup, E. C, Simmons, M., and Tashkin, D P. (1998) Histo- 
pathologic and molecular alterations in bronchial epithelium in habitual smokers of mari- 
juana, cocaine, and/or tobacco. /. Natl. Cancer Inst. 90, 1198-1205. 

24. Morris, R. R. (1985) Human pulmonary histopathological changes from marijuana smok- 
ing. J. Forensic Sci. 30, 345-349. 

25. Roth, M. D., Baldwin, G. C, and Tashkin, D. P. (2002) Effects of delta-9-tetrahydrocan- 
nabinol on human immune function and host defense. Chem. Phys. Lipids 121, 229-239. 

26. Isenschmid, D. S. and Caplan, Y. H. (1988) Incidence of cannabinoids in medical exam- 
iner urine specimens. J. Forensic Sci. 33, 1421-1431. 

27. Huestis, M. A., Henningfield, J. E., and Cone, E. J. (1992) Blood cannabinoids. II. Models 
for the prediction of time of marijuana exposure from plasma concentrations of delta 9- 
tetrahydrocannabinol (THC) and 1 l-nor-9-carboxy-delta9-tetrahydrocannabinol 
(THCCOOH). J. Anal. Toxicol. 16, 283-290. 

28. Huestis, M. A., Henningfield, J. E., and Cone, E. J. (1992) Blood cannabinoids. I. Absorp- 
tion of THC and formation of 1 1-OH-THC and THCCOOH during and after smoking mari- 
juana. J. Anal. Toxicol. 16, 276-282. 

29. Giroud, C, Menetrey, A., Augsburger, M., Buclin, T., Sanchez-Mazas, P., and Mangin, P. 
(2001) Delta(9)-THC, 1 l-OH-delta(9)-THC and delta(9)-THCCOOH plasma or serum to 
whole blood concentrations distribution ratios in blood samples taken from living and dead 
people. Forensic Sci. Int. 123, 159-164. 

30. Leuschner, J. T., Harvey, D. J., Bullingham, R. E. S., and Paton, W. D. M. (1986) Pharma- 
cokinetics of delta 9-tetrahydrocannabinol in rabbits following single or multiple intrave- 
nous doses. Drug Metab. Dispos. 14, 230-238. 

31. Nyoni, E. C, Sitaram, B. R., and Taylor, D. A. (1996) Determination of delta 9-tetrahydro- 
cannabinol levels in brain tissue using high-performance liquid chromatography with elec- 
trochemical detection. J. Chromatogr. B Biomed. Appl. 679, 79-84. 

32. Moffat, A., Osselton, D., and Widdop, B. (eds.) (2004) Clarke's Analysis of Drugs and 
Poisons in Pharmaceuticals, Body Fluids and Postmortem Material, 3rd ed., Vol. 2, Phar- 
maceutical Press, London, pp. 740-743. 



Chapter 14 



Cannabinoid Effects 

on Biopsy etiological, Neuropsychiatries 

and Neurological Processes 

Richard E. Musty 

1. Introduction 

There have been several reviews of the therapeutic potential of both natural and 
synthetic cannabinoids (1,2). These reviews strongly suggest potential therapeutic 
effects of cannabinoids in motivational processes and their associated disorders (hun- 
ger, appetite, pain), psychological disorders (anxiety, depression, bipolar disorder, 
schizophrenia, alcohol dependence), and central nervous system (CNS) disorders (vom- 
iting and nausea, spasticity, dystonia, brain damage, epilepsy). This chapter, for the 
most part, covers developments since these reviews were published. 

2. Hunger and Appetite 

Cannabis was reported to be an appetite stimulant as early as 1845 by Donovan 
(3), suggesting that it might be used for anorexia nervosa. Although it is common 
knowledge that cannabis stimulates hunger, very little research has been accomplished 
over subsequent years.Van Den Broek et al. (4) administered 9-aza-cannabinol to sheep 
intravenously and found that feeding behavior was increased along with a decrease in 
gastric secretion. 

Foltin et al. (5) tested nine normal subjects in a live-in laboratory setting. He 
found that administration of two or three active marijuana cigarettes (1.84%) during a 
time when subjects could smoke in a social setting increased caloric intake as a result 
of between-meal snack food, but not during regular meals. These data seem to be the 

From: Forensic Science and Medicine: Marijuana and the Cannabinoids 
Edited by: M. A. ElSohly © Humana Press Inc., Totowa, New Jersey 

303 



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most objective test of the appetite/hunger-stimulating effects of cannabinoid agonists 
(see also ref. 6). 

Beal et al. (7) examined the effects of dronabinol on 94 late-stage AIDS patients 
who received dronabinol orally 2.5 mg twice daily (90%) or 2.5 mg once daily (10%) 
for 12 months. Appetite was measured using a visual analog scale for hunger. They 
found an increase in appetite of 48.6-76.1%, which peaked at 4 months, after which 
dronabinol induced appetite increases of at least double that at baseline and stable 
weight for the remaining months. These data seem to suggest that dronabinol stimu- 
lates appetite and leads to maintained weight in advanced AIDS patients. Further re- 
search in this area is certainly needed, especially in patients earlier in the progression 
of the disease. 

2.1. Appetite Supression 

Sanofi-Aventis (8) reported the following concerning the effects of the cannab- 
inoid type 1 (CB[) receptor antagonist SR141716, now known as rimonabant (also 
Acomplia™). 

The results of a 2-year phase III study in 3040 patients with rimonabant 
(Acomplia), the first in a new class of therapeutic agents called selective CB, blockers, 
demonstrate that the benefits achieved with rimonabant 20 mg at the end of the first 
year of the study were sustained in the second year of therapy with a good safety and 
tolerability profile vs placebo. Patients treated with rimonabant 20 mg for 2 years 
experienced a reduction in body weight and in waist circumference, demonstrating a 
significant reduction in abdominal fat, a key marker for cardiovascular disease. 
Patients treated with rimonabant 20 mg over the 2-year period also achieved a 
significant increase in high-density lipoprotein (HDL) cholesterol (good cholesterol), 
a reduction in triglycerides, and an improvement in insulin sensitivity. The RIO- 
North America study is the largest of all rimonabant studies presented to date. The 
results from this study are consistent with the findings from two previous large-scale 
studies on rimonabant-RIO-Lipids and RIO-Europe-communicated earlier this year 
and add to the ever-growing body of evidence supporting the drug's efficacy and tol- 
erability profile. Rimonabant is currently being developed for the management of car- 
diovascular risk factors, including reduction of abdominal obesity, improving lipid 
and glucose metabolism, and as an aid to smoking cessation. 

Obesity is a major public health burden and one of the most frequent causes of 
death worldwide, mainly through cardiovascular disease. Obesity is typically mea- 
sured by body mass index. However, recent findings have shown that visceral 
(abdominal) fat (simply measured by waist circumference) is a better predictor for 
heart attack than weight or body mass index. Forty-four percent of adult Americans 
have a waist circumference size exceeding the at-risk level (40 in. for men and 35 in. 
for women). Visceral fat is associated with the cause of metabolic risk factors such as 
dyslipidemia or insulin resistance that may lead to diabetes, heart attack, stroke, and 
other cardiovascular disease. Reducing abdominal fat is a recognized priority for pre- 
venting cardiovascular disease. 

RIO-North America was a phase III, multinational multicenter, randomized, 
double-blind, placebo-controlled trial comparing two fixed-dose regimens of 
rimonabant (5 and 20 mg once daily) to placebo for a period of 2 years. The study was 
conducted in 3040 patients at 72 centers in the United States and Canada. 



Cannabinoid Effects on Mental Processes 



305 



The objectives of the trial were to assess the effect of rimonabant on weight loss 
over a period of 1 year and to determine the ability of rimonabant to prevent weight 
regain during a second year of treatment. The study objectives also included an 
assessment of improvement in risk factors associated with abdominal obesity (as mea- 
sured by waist circumference), such as dyslipidemia, glucose metabolism, and the 
metabolic syndrome, and an evaluation of the safety and tolerability of rimonabant 
over a period of 2 years. 

After a screening period of 1 week, patients were prescribed a mild hypocaloric 
diet (designed to reduce daily caloric intake by 600 kcal from the patient's energy 
requirements) and entered a 4-week single-blind placebo run-in period. Afterward, 
patients were randomly allocated to one of the three treatment groups: placebo or 
rimonabant 5 or 20 mg for 52 weeks of double-blind treatment using a randomization 
ratio of 1:2:2. 

After the first year of treatment, patients who received rimonabant 5 or 20 mg 
were rerandomized to either the same dose of rimonabant or placebo using a random- 
ization ratio of 1:1 for an additional 52-week treatment period (the placebo group 
remained on placebo during the second year). 

2.2. Rio-North America Findings 

The findings show that 2-year treatment with rimonabant 20 mg significantly 
lowered weight, reduced abdominal fat, diminished cardiovascular risk factors, and 
decreased metabolic disorders in this patient population. Waist circumference, a simple 
measure of abdominal fat, in patients treated with rimonabant 20 mg for the full 2- 
year period was reduced by 8 cm (3.1 in.) vs 4.9 cm (1.9 in.) for rimonabant 5 mg and 
3.8 cm (1.5 in.) in the placebo group (p < 0.001). Of the patients who received treat- 
ment with rimonabant 20 mg throughout the 2-year period, 62.5% lost more than 5% 
of their initial body weight vs 36.7% of those on rimonabant 5 mg and 33.2% of those 
on placebo (p < 0.001). In the same period, 32.8% of patients treated with rimonabant 
20 mg lost in excess of 10% of their initial body weight vs 20% of those on rimonabant 
5 mg and 16.4% of patients on placebo (p < 0.001). 

Metabolic parameters were also significantly improved in patients treated with 
rimonabant 20 mg throughout the 2-year period, with HDL cholesterol increased by 
24.5% in the rimonabant 20 mg group vs 15.6 and 13.8% in the rimonabant 5 mg and 
placebo groups, respectively (p < 0.001). Triglycerides were reduced by 9.9% in patients 
treated with rimonabant 20 mg throughout the 2-year period vs 5.9 and 1.6% in the 
rimonabant 5 mg and placebo groups, respectively (p < 0.05). 

Although diabetic patients were not included in the study, patients on rimonabant 
20 mg had significantly improved their insulin sensitivity compared to those on 
rimonabant 5 mg and on placebo. The effect of rimonabant on HDL cholesterol, trig- 
lycerides, fasting insulin, and insulin sensitivity (as measured by homeostasis model 
assessment) appeared to be twice that which would be expected from the degree of 
weight loss achieved (all p < 0.05). Of particular note is that the number of patients 
diagnosed with metabolic syndrome at baseline and treated with rimonabant 20 mg 
over the 2-year study period was reduced by more than one third (p < 0.001). Meta- 
bolic syndrome encompasses a series of serious health risks or conditions that increase 
a person's chance to develop heart disease, stroke, and diabetes. 



306 



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2.3. A Good Safety and Tolerability Profile 

Rimonabant 20 mg proved to be safe and tolerable vs placebo throughout the 2- 
year study period. Side effects were mainly minor and short-lived. Overall discontinu- 
ation rates for adverse events in the first year of the study were 7.2, 9.4, and 12.8% in 
the placebo, rimonabant 5 mg, and rimonabant 20 mg groups, respectively. The dis- 
continuation rates for patients randomly assigned to continue their first-year treatment 
for a second year were 6.7, 8.3, and 6.0% in the placebo, rimonabant 5 mg and 20 mg 
groups, respectively. No differences were noted in the three groups with regard to 
scores measured by the Hospital Anxiety Depression scale. In this trial and in two 
preceding studies, rimonabant was also shown to have no significant electrocardio- 
gram or heart rate changes. 

2.4. Rimonabant and the Endocannabinoid System 

The Endocannabinoid (EC) System is a newly discovered physiological system 
in the body that is believed to play a key role in the central and peripheral regulation 
of energy balance, glucose and lipid metabolism, as well as in the control of tobacco 
dependence. CB, receptors are found in the brain as well as in peripheral tissues of the 
body, such as adipocytes (or "fat cells"), which are associated with lipid and glucose 
metabolism. Excessive food intake or chronic tobacco use results in an overactive EC 
system. This can trigger a cycle of increased eating and fat storage or, in the case of 
smoking, sustained tobacco dependence. 

Rimonabant is the first in a new class of drugs called CB, blockers. By selec- 
tively blocking both centrally and peripherally the CB, receptors, rimonabant modu- 
lates the overactive EC System. The results have been seen in reducing cardiovascular 
risk factors through reduction in abdominal fat and a corresponding improvement in 
metabolic parameters that is beyond that expected through weight reduction. 

The new clinical results from the RIO-North America study further suggest that 
rimonabant may become an important tool in the cardiovascular risk factor reduction 
armamentarium. 

LeFur (6) reviewed a number of findings that support the effects of the mecha- 
nisms by which rimonabant acts: 

1. CB, receptors are located in brain areas associated with hunger and appetite. 

2. "Endocannabinoids may tonically activate the CB, receptors to maintain food intake, 
and increase the incentive value of food as well as reinforcing the rewarding effects of 
nicotine involving the brain reward circuits..." 

3. In mutant obese mice, rimonabant decreased food intake and led to a sustained loss in 
body weight. 

4. Rimonabant had no effect in CB, receptor knockout mice, confirming the fact that 
CB, receptors are necessary for the action of this drug. 

To conclude, it seems that cannabinoid agonists increase hunger and appetite, 
whereas antagonists decrease appetite and hunger. There seems to be significant promise 
for both stimulating appetite and decreasing it. If these results continue to show prom- 
ise, medications of significant value might be developed. 



Cannabinoid Effects on Mental Processes 



307 



3. Pain 

In a review, Walker et al. (9) concluded that cannabinoids suppress nociceptive 
neurotransmission, synthetic agonists are as potent as morphine, there are both direct ef- 
fects on spinal cord, the periphery, and the brain. 

Bicher and Mechoulam (10) found that A 9 -tetrahydrocnnabinol (THC) and A 8 - 
THC (ip) were about half as effective as morphine (sc) on three tests of analgesia: the 
hot plate test, the acetic acid writhing test, and the tail flick test. In a review of human 
anecdotal studies and controlled studies (11), pain relief has been reported anecdot- 
ally as well as in controlled studies. Of the four double-blind placebo-controlled stud- 
ies reviewing THC administration for cancer pain, THC was effective at 15 and 20 mg 
in one study and in the second study was more effective than placebo and THC for 
postoperative pain: levonatradol was effective at 1.5-3 mg, and THC was not effec- 
tive at doses of 0.22 and 0.44 mg/kg (pain after extraction of impacted molar teeth). In 
a questionnaire study, Dunn and Davis (12) reported that patients who smoked can- 
nabis found relief from phantom limb pain. In a single case report, Finnegan-Ling and 
Musty (13) reported that THC p.o. was more effective than conventional pain medica- 
tions, including opiates and nonsteroidal anti-inflammatory drugs. 

Very few studies have examined the effects of extracts with a low THC/canna- 
bidiol (CBD) ratio or experimentally varied pure THC and CBD mixtures. Sofia et al. 
(14) conducted a comparison of the pain-relieving effects of A 9 -THC, a crude mari- 
huana extract (CME), cannabinol (CBN), CBD, morphine SO-4, and aspirin (all po). 
They used the acetic acid induced writhing test, the hot plate test, and the Randall- 
Selitto paw pressure tests in rats. A 9 -THC and morphine were equipotent in all tests 
except that morphine was significantly more potent in elevating pain threshold in the 
uninflamed rat hind paw. In terms of A 9 -THC content, CME was nearly equipotent in 
the hot plate and Randall-Selitto tests, but was three times more potent in the acetic 
acid writhing test. On the other hand, CBN, like aspirin, was only effective in reduc- 
ing writhing frequency in mice (three times more potent than aspirin) and raising the 
pain threshold of the inflamed hind paw of the rat (equipotent with aspirin). CBD did 
not display a significantly analgesic effect in any of the test systems used. The results 
of this investigation seem to suggest that both A 9 -THC and CME possess analgesic 
activity similar to morphine, whereas CBN appears to be a nonanalgesic at the doses 
used. Only one human case study that used an extract with known amounts of THC, 
CBD, and CBN (15) has been published prior to reports with orally administered 
extracts. The extract contained THC (5.75%), CBD (4.73%), and CBN (2.42%). They 
administered an oral extract to a person with chronic abdominal pain associated with 
familial Mediterranean fever in a 6-week randomized placebo-controlled study. Both 
normal use of morphine and escape use (dosing when an acute attack of pain occurs) 
were significantly reduced. Self-reports on the visual analog scale also demonstrated 
significant reductions in perception of pain. 

Recently there have been several studies suggesting therapeutic potential for CB , 
and CB 2 agonists. 

Dogrul et al. (16) reported that diabetic neuropathic pain is common and is resis- 
tant to morphine treatment. Strep tozotocin (200 mg/kg) was used to induce diabetes in 
mice, which were tested between 45 and 60 days after onset of diabetes. Antinociception 



308 



Musty 



was measured using the radiant tail flick test, Von Frey filaments, and the hot-plate 
test, respectively. Tactile allodynia but not thermal hyperalgesia was found. WIN 55- 
212-2a, a cannabinoid receptor agonist that acts in the CNS but is not inhibited by the 
CB, antagonist AM 251, produced a dose-dependent decrease in allodynia at doses of 
1,5, and 10 mg/kg. 

Ibrahim et al. (17) tested the effects of AM 1241 (a selective CB 2 receptor ago- 
nist) on experimental neuropathic pain in rats. Tactile hypersensitivity and thermal 
hypersensitivity were induced by ligation of L5 and L6 spinal nerves. AM 1241 dose- 
dependently reversed hypersensitivity. When tested in knockout mice using the 
same ligation procedure, AM 1241 was effective in reducing pain sensitivity, suggest- 
ing that this peripherally active agonist blocks neuropathic pain. The authors suggest 
that CB 2 receptor agonists, devoid of CNS activity, are predicted to be effective with- 
out the CNS side effects of centrally acting cannabinoid agonists. 

Johanek and Simone (18) examined whether or not cannabinoids attenuated 
hyperalgesia produced by a mild heat injury to the glabrous hind paw and if the 
antihyperalgesia was receptor-mediated. Mild heat injury (55°C for 30 seconds) to 
one hind paw was given to anesthetized rats. Fifteen minutes after injury, decreased 
withdrawal latency to radiant heat and increased withdrawal frequency to a von Frey 
monofilament (200 mN force) delivered to the injured hindpaw was observed. 
Intraplantar injection of vehicle or the agonist WIN 55,212-2 (1, 10, or 30 [ig in 100 |iL) 
decreased heat and and mechanical hyperalgesia in a dose-dependent fashion, whereas 
the inactive enantiomer WIN 55,212-3 did not. The CB, receptor antagonist AM 251 
(30 [ig) co-injected with WIN 55,212-2 (30 tig) decreased the antihyperalgesic effects 
of WIN 55,212-2,. and CB 2 receptor antagonist AM 630 (30 [ig) co-injected with WIN 
55,212-2 decreased the antihyperalgesic effects of the agonist. Injection of WIN 55,212- 
2 into the contralateral paw did not change heat-injury-induced hyperalgesia. These 
results suggest that antihyperalgesia was mediated by peripheral mechanisms. The 
authors conclude, like Ibrahim (17), that this reduction of hyperanalgesia may be 
peripheral. 

Nackley et al. (19) examined the effects of CB,-selective cannabinoid agonist 
AM 1241 on activity in spinal wide dynamic range neurons by transcutaneous electri- 
cal stimulation urethane-anesthetized rats during either carrageenan inflammation or 
not. Intravenous administration decreased activity in wide dynamic range neurons 
induced by stimulation. This effect was blocked by the CB 2 antagonist SR 144528 but 
not by the CB[ antagonist SR141716A. In addition, activity of nonnociceptive neu- 
rons recorded in the lumbar dorsal horn was not affected by AM1241. 

In a recent report, Chichewizc and Welch (20) found that A 9 -THC (20 mg/kg) 
and morphine (20 mg/kg) induced analgesia in both vehicle-treated and morphine- 
tolerant mice. In both groups analgesia was equally effective, "indicating that analge- 
sia produced by the combination is not hampered by existing morphine treatment (no 
cross tolerance to the combination)." Mice were tested with A 9 -THC (20 mg/kg) and 
morphine (20 mg/kg) twice daily for 6.5 days and tested for tolerance, and on day 8, 
A 9 -THC tolerance was observed, but morphine tolerance did not occur. These results 
suggest that low-dose combinations of A 9 -THC and morphine might prevent morphine 
tolerance. The authors conclude that combinations of these drugs may be useful in 
chronic pain patients over morphine administration alone. 



Cannabinoid Effects on Mental Processes 



309 



In summary, animal research indicates that there are potential effects on the con- 
trol of pain at many different levels of analysis. Some of these results are supported by 
human studies, to be discussed later. Others must await clinical trials, assuming toxic- 
ity and safety standards are met. 

3.1. Human Studies 

Brenneisen et al. (21) administered multiple does of either THC capsules 
(Marinol®) or THC hemisuccinate suppositories at 24-hour intervals to two patients 
who had spasticity due to organic damage. They found that the oral bioavailability 
was 45-53% compared with the rectal route of administration, because the oral route 
involves less absorption and higher first-pass metabolism. Both patients experienced 
lower pain (self-rated) and decreased spasticity and rigidity as measured by the 
Ashworth Scale and walking ability. Passive mobility also improved. Using physi- 
ological and psychological testing, no differences were found in cardiovascular func- 
tioning, ability to concentrate, or mood. Finally, the comparative effectiveness of the 
oral form of administration was 25-50% of the rectal route. 

Wade et al. (22) conducted a study testing the effects of plant-derived CME, 
administered by buccal spray. Using a double-blind drug and placebo, single -patient 
randomized crossover design, patients were administered the extracts THC, CBD, 1:1 
CBD:THC by self-titration to doses providing symptom relief with the lowest possible 
unwanted side effects. Doses to achieve relief were highly individual, ranging from 2.5 
to 120 mg in a 24-hour period. Patients included 18 with multiple sclerosis (MS), 4 with 
spinal cord injury, and one each with brachial plexus damage (7) and limb amputation. 
Pain relief was measured using visual analog scales. THC, CBD, and the combination 
were significantly superior to placebo. Impaired bladder control, muscle spasms, and 
spasticity were improved by CME in some patients with these symptoms. 

Brady et al. (23) tested the effects of cannabis-based medicinal extracts in patients 
with advanced MS who had developed troublesome lower urinary tract symptoms. 
Using an open-label design, THC and CBD (2.5 mg of each per oral spray) for 8 
weeks followed by THC only (2.5 mg THC per oral spray) for a further 8 weeks and 
then into a long-term extension were taken by the patients. Fifteen patients were evalu- 
ated using the following measures: urinary frequency and volume charts, incontinence 
pad weights, cystometry and visual analog scales for secondary troublesome symp- 
toms. Significant decreases in urinary urgency, the number and volume of inconti- 
nence episodes, frequency nocturia, and daily total voided occurred in patients. 
Self-assessment of spasticity, pain, and quality of sleep improved continuously for a 
35-week period with both extracts. 

Burstein et al. (24) reported that ajulemic acid, also known as CT-3 and IP-751, 
derived from the major metabolite of THC, had many of the properties of the nonste- 
roidal anti-inflammatory drugs and is apparently free of the intoxicating effects of 
THC. In healthy patients and those with neuropathic pain, no psychotropic effects 
were found. In short-term trials of 1 week, pain was reduced in patients with neuro- 
pathic pain using a visual analog scale. Neither normal subjects nor pain patients 
experienced any signs of either dependence or withdrawal. These data suggest that 
ajulemic acid has therapeutic potential in the treatment of chronic pain. 



310 



Musty 



Zajicek et al. (25) evaluated the effects of THC (Marinol) and a cannabis extract 
(oral Cannador, a capsule with THC and an unstated amount of cannabidiol) in pa- 
tients with MS in a multicenter randomized placebo-controlled trial. They found no 
effects on the Ashworth Scale in the 611 patients in the trial, but objective improve- 
ment in mobility and reduction in pain occurred. One problem with this study is that 
both THC and Cannador are poorly absorbed, which might explain the differences 
between buccal spray administration and oral administration. 

Svendsen et al. (26) tested the effects of dronabinol in patients with MS in a 
randomized double-blind placebo-controlled crossover trial for 3 weeks followed by a 
3-week washout period, then crossover to either drug or placebo for the final 3 weeks. 
Twenty-four patients were enrolled through an outpatient clinic. Drug doses were 
adjusted to a maximum dose of 10 mg daily. Using a numerical pain scale, scores were 
significantly measured during the last week of treatment when compared with the 
placebo condition. Dizziness occurred frequently during the first week of treatment. 
Although the authors comment correctly that pain reduction was moderate in this study, 
the design of the study did not allow patients to self-titrate doses of dronabinol, prob- 
ably minimizing the efficacy of pain reduction achieved by the patients. 

In summary, it seems that cannabinoid agonists have potential for therapeutic 
use in pain and MS. This is supported by the reports of GW Phamaceuticals discussed 
in the next section. 

4. Various Potential for Natural Cannabinoids 

GW Pharmaceuticals (27) has an ambitious program testing a natural cannab- 
inoid mixture, Sativex® (THC:CBD ratio 1.1), in the form of an oral spray. Applica- 
tions for regulatory approval have been approved in Canada for neuropathic pain and 
for symptoms of MS. Regulatory findings will be submitted in the United Kingdom. 
Figure 1 shows the drug-development progress as of mid-2004. Note that Sativex is 
presently in phase III trials for spinal cord injury and bladder dysfunction and in phase 
II trials for diabetic neuroropathy. High-THC extracts are in various stages of devel- 
opment for several types of pain. In addition, extracts high in CBD are also in various 
stages of development. 

5. Psychological Disorders (Anxiety, Depression, Bipolar 
Disorder, Schizophrenia, Alcohol Dependence) 

5.1. Anxiety 

In a review, Musty (28) concluded that for CB, antagonists, it seems that the 
preponderance of the data suggest that these compounds are anxiolytic. Agonists, on 
the other hand, seem to have biphasic effects: low doses seem to be anxiolytic, high 
doses anxiogenic. In addition, it seems that the context is important. Further research 
is needed to sort out the differences among various studies, but it is clear that both 
antagonists and agonists on the CB( receptor have anxiolytic properties. Standardiza- 
tion of testing procedures across laboratories might be helpful, the problem being that 



Cannabinoid Effects on Mental Processes 



311 



PRODUCT 


INDICATION 


s re-clin Phase 


Phase II Phase 111 


Submit 


Approval 


Sativex 


Multiple Sclerosis 












THC;CBD 


MS Pain 








(1:1 ratio) 


MS Spasticity 
MS Bladder 








Peripheral Neuropathic Pain 

Allodynia 

Diabetic Neuropathy 


























Central Neuropathic Pain 
















MS 




— 






Brachial Plexus 










OUIIIdl UUIU IIMUly 








High CBD 


Cancer Pain 
Rheumatoid Arthritis 










ratios 


Inf lammatory Bowel Diseases 
Neurogenic Symptoms 
Psychotic Disorders 
CNS (Epilepsy / Neuroprotection) 














HighTHC 


Post-operative Pain 
Chronic Pain 














THC-V 


Neurotherapeutics 














Methadone 
Diamorphine 


Drug Dependency 
Drug Dependency 















Fig. 1. Progress on preclinical and clinical trails of cannabinoid products by GW 
Pharmaceuticals. 



there are many variables that have not been explored with behavioral methods used to 
test for anxiolytic properties. Because it is widely known that activation and inactiva- 
tion of CB[ receptors has a multitude of modulatory effects on neurotransmitter sys- 
tems, it would be advantageous for researchers to examine what changes in 
neurotransmitter activity occur in conjunction with the pharmacological effects con- 
served in the types of studies. There seems to be quite a convergence between animal 
research and human research, strongly suggesting that CBD is a true anxiolytic. Given 
the fact that this drug has no psychoactivity in terms of intoxication and is very safe, it 
seems important to pursue the potential of CBD with vigor, with further behavioral 
pharmacological studies, mechanistic studies employing neuropharmacological meth- 
ods, and clinical studies. 

5.2. Depression 

In a review by Musty (11), the following summaries of research on depression, 
bipolar disorder, schizophrenia, and alcohol dependence are presented: 

In a study of normal subjects, Musty (29) found a positive correlation on the 
depression scale of the Minnesota Multiphase Personality Inventory with feelings of 
euphoria after smoking marijuana, while there was no correlation between anxiety 
(hysteria scale) and somatic concerns (hypochondriasis scale) with feeling euphoric, 
suggesting an antidepressive effect from marijuana use. Schnelle et al. (30), in a sur- 
vey of 128 patients in Germany, reported 12% used marijuana for relief of depression. 



312 



Musty 



Consroe et al. (31) found that depression was reduced in patients with MS in a self- 
report questionnaire. In another self-report study (32) of patients with spinal cord in- 
juries, similar reductions in depression were reported. In cancer patients Regalson 
(33) found that THC relieved depression in advanced cancer patients. Finally, Warner 
et al. (34) found reported relief from depression in a survey of 79 mental patients. At 
present, there are very few data supporting the hypothesis that cannabinoids might 
relieve depression, but tests of both agonists and antagonists of the CB, receptor are 
clearly indicated to test this hypothesis. 

Since the Musty review (11), Musty et al. ( 35) discovered that cannnabichromene 
selectively blocks behavioral despair in a mouse model of depression. This is a novel 
finding in that there has been very little work published on the effects of 
cannnabichromene. 

5.3. Bipolar Disorder 

Grinspoon and Bakalar (36,37) presented six case studies of people with bipolar 
disorder using cannabis to treat their symptoms. Some used it to treat mania, depres- 
sion, or both. They stated that it was more effective than conventional drugs or helped 
relieve the side effects of those drugs. One woman found that cannabis curbed her 
manic rages. Others described the use of cannabis as a supplement to lithium (allow- 
ing reduced consumption) or for relief of lithium's side effects. 

These clinical observations are important leads to the potential use of cannab- 
inoids for manic depressive disorder and suggest that clinical trials should be con- 
ducted. 

5.4. Schizophrenia 

5.4.1. Animal Studies 

Zuardi et al. (38) tested the effects of CBD and haloperidol in a model that pre- 
dicts antipsychotic activity in rats. Apomorphine induces stereotyped sniffing and bit- 
ing. Both drugs decreased the frequency of these behaviors. CBD did not induce 
catalepsy, even at very high doses, although haloperidol induced catalepsy. The authors 
conclude that CBD has a pharmacological profile similar to the atypical antipsychotic 
drugs. 

Musty et al. (2) tested the effects of the of the CB, receptor antagonist SR141716 
in two animal models of schizophrenia. In the first, ibotenic acid lesions of the hip- 
pocampus were made in neonatal rats, which results in a brain degeneration pattern 
similar to that observed in schizophrenics as well as abnormal play behavior in an 
anxiety-provoking environment. In a second model, ketamine-induced enhancement 
of prepulse inhibition was tested. In both of these tests, SR14171 6 reversed the abnor- 
mal behavior. These findings in animal models are consistent with the hypothesis that 
CB, receptor antagonists have antipsychotic activity. 

5.4.2. Human Studies 

The use of cannabis has been associated with exacerbation of symptoms of schizo- 
phrenia (39), but other reports suggest that the use of cannabis helped patients manage 
their symptoms of schizophrenia, but several studies have shown potential symptom- 
relieving effects of cannabis use. 



Cannabinoid Effects on Mental Processes 



313 



Peralta and Cuesta (40) studied 95 schizophrenics who had used cannabis in the 
last year. They found lower scores in the schizophrenics on delusions and alogia scales 
of Andreasen's Scales for the Assessment of Positive and Negative Symptoms, sug- 
gesting that cannabis may affect the negative symptoms of schizophrenia. In a sample 
of community-based mentally ill patients, Warner et al. (34) reported fewer hospital 
admissions and fewer symptoms of anxiety, depression, and insomnia among users 
preferring marijuana. 

Zuardi and Morais et al. (41) reported an experiment in a single case, in which 
the patient was being treated with haloperidol. The medication was stopped as a result 
of side effects followed by a return of symptoms, leading to hospitalization. At this 
point the patient was given placebo medication for 4 days, after which she was admin- 
istered CBD (two doses per day) on an increasing dose schedule up to 750 mg/dose 
until the 26th day. This was followed by 4 days of placebo and finally by a return to 
haloperidol for 4 weeks. Interviews were conducted and videotaped, which was fol- 
lowed by rating of interviews using the Brief Psychiatric Rating Scale (BPRS) and the 
Interactive Observation Scale for Psychiatric Patients (IOSPP). A psychiatrist rated 
the patient, blind to treatment conditions on the BPRS, and nurse assistants indepen- 
dently, and blind to treatment conditions rated the patient on the IOSPP. Comparing 
placebo to the CBD condition, Hostility-Suspiciousness dropped by 50% of the BPRS 
maximum scale score, Thought Disturbance by 37.5%, Anxiety-Depression by 43.7%, 
Activation by 41.6%, and Anergia by 31.3%. During 4 days of placebo that followed, 
all four scale scores increased somewhat. The patient was then returned to haloperidol 
treatment, and the subsequent scores were close to those with CBD treatment. This 
experiment demonstrates that antagonists of the CB , receptor are candidates for test- 
ing in human schizophrenia. 

5.5. Alcohol Dependence 

Musty (42) found that CBD, A 9 -THC, and clonidine reduced body tremor and 
audiogenic seizures during alcohol withdrawal in C57B16J mice forced to become 
alcohol tolerant on a liquid diet containing alcohol. Equivalent reductions in tremors 
and seizures were found with clonidine. Grinspoon and Bakalar (36) reported two 
cases of individuals who used marijuana to deal with alcohol dependence. 

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Index 



AcompliaTM, see Rimonabant 

Acquired immunodeficiency syndrome (AIDS), 

marijuana effects on progression, 238, 

239 

Acute coronary syndrome, marijuana as trigger, 

297, 298 
Addiction, 

endocannabinoid system in addiction to 

other drugs, 133-135 
marijuana withdrawal management, 132, 
133 

neural pathways, 113 

opioid receptors in cannabinoid dependence, 
133, 134 

tolerance and dependence, 113, 114, 245, 246 
Adipose tissue testing, 

mass spectrometry, 184 

rationale, 297 
2-AG, see 2-Arachidonoyl glycerol 
AIDS, see Acquired immunodeficiency 

syndrome 
Alcohol, 

dependence and marijuana management, 313 
endocannabinoid system and intake, 134 
marijuana combination and impairment, 213 
Alcohols, Cannabis composition, 36 
Alkaloids, Cannabis composition, 29 
Alveolar macrophage, marijuana effects, 

258-260, 268, 269 
AM 1241, analgesia, 308 
Amygdala, CB1 receptors, 109 
Analgesia, 

cannabinoid agonist studies, 307-309 



cannabinoid receptor agonists, 130-132 
CB! receptors, 112, 113, 130-132 
endogenous cannabinoid system, 130 
human studies of THC, 309, 310 
pain pathways, 110, 112 
THC efficacy, 307 

Anandamide, 

neuromodulation, 97-99 
synthesis, 98, 127 

Anxiety, cannabinoid antagonist studies, 310, 
311 

Apigenin, pharmacology, 40 
Appetite, 

cannabinoid effects, 303, 304 
endogenous cannabinoid system in 

homeostasis, 128, 129 
rimonabant and suppression, 304, 305 
THC effects, 129 
Arachidonoyl ethanolamide, neuromodulation, 
97-99 

2-Arachidonoyl glycerol (2-AG), 
neuromodulation, 97-99 
synthesis, 98 
vasodilatation, 116 

B-cell, cannabinoid effects, 263, 264 
Bipolar disorder, marijuana effects, 312 
Blood pressure, cannabinoid effects, 115, 116, 

239 
Blood testing, 

cause-of-death determination, 299 
driving impairment testing, 
11-carboxy-THC, 283, 284 



377 



318 



Index 



THC, 283, 284 

THC/ll-carboxy-THC ratio, 284, 285 
interpretation of plasma tests, 212-217 
mass spectrometry, 182-184, 192, 193 
Bupropion, marijuana withdrawal studies, 132 

Cannabichromene, 

antidepressant activity, 312 
biosynthesis, 7 
features, 18 
Cannabicyclol, features, 22 
Cannabidiol (CBD), 
anxiolytic activity, 311 
biosynthesis, 7 
features, 18, 19 
indica content, 1 1 
medical marijuana content, 11, 12 
pharmacology and activity, 39 
schizophrenia studies, 312, 313 
Cannabidiolic acid, features, 18, 19 
Cannabielsoin, features, 22 
Cannabigerol, 
biosynthesis, 7 
features, 18 
Cannabigerovan, biosynthesis, 7 
Cannabinodiol, features, 23 
Cannabinoid receptors, 

agonist studies of analgesia, 307-309 
antagonists, see Rimonabant 
receptors, 
addiction role, 113, 114 
cardiovascular system, 116 
distribution, 101, 126 
knockout mice, 101, 112, 117, 133 
limbic system, 109, 110 
motor function, 103, 104, 106, 107 
peripheral blood leukocyte expression, 263, 

264, 298 
signaling, 99-101, 127 
splice variants, 99 
types, 99, 126, 127, 297 
Cannabinoid test system, features, 150, 151 
Cannabinol, 
analgesia, 307 
features, 23 



Cannabis, see also Indica, 

chemical fingerprinting for source 

identification, see Chemical fingerprinting, 

Cannabis 
color spot tests, 42 
compound biosynthesis, 6, 7 
domestication and dispersal, 8, 9, 14 
drugs-of-abuse testing, see Immunoassays, 

Cannabis; Mass spectrometry 
ecology, 1, 2 

epidemiology of use, 237, 253, 286, 295 
life cycle, 1, 2 

medical marijuana, see Medical marijuana 
microscopy, 41, 42 
origin, 8 
production, 

drug breeding, 9, 10 

field crop, 2, 4 

greenhouse and grow room, 4, 5 
resin gland anatomy and development, 5, 6 
species taxonomy, 9 
Cannabis psychotic disorder, features, 245 
Cannabitriol, features, 24 
Cannachromavarin, biosynthesis, 7 
Carbohydrates, Cannabis composition, 30, 31 
Cardiovascular disease, epidemiology, 295 
CB! receptor, see Cannabinoid receptors 
CBD, see Cannabidiol 

CEDIA, see Cloned enzyme donor immunoassay 
Cervical cancer, risks in marijuana users, 247 
Chemical fingerprinting, Cannabis, 

age and sex of plants, 61 

chemometrics, 53, 54 

compounds of interest, 54, 55 

daughter plants grown in a different region, 61 

experimental design, 56, 57 

extraction, 57, 58 

gas chromatography /mass spectrometry, 58 

hashish analysis, 62 

indoor versus outdoor plants, 60, 61 

multivariate data analysis, 58, 59 

overview, 51-53 

phase II study, 59-63 

prospects, 63, 64 

storage condition effects, 61 



Index 



319 



Cloned enzyme donor immunoassay (CEDIA), 

principles, 148 
Cognitive function, marijuana effects, 243-245, 

278, 279 
Color spot tests, Cannabis, 42 
Cytokines, cannabinoid effects, 264-266, 270 

DAT, see Drugs-of-abuse testing 

Dependence, see Addiction 

Depression, marijuana effects, 311, 312 

Dihydrotestosterone, marijuana smoke 
condensate antagonism, 94 

DNA testing, Cannabis, 43 

Driving impairment, 

alcohol and marijuana combination, 213 
cognitive effects of marijuana, 278, 279 
epidemiology of marijuana and driving, 
286 

field sobriety testing, 280, 281 
hallucinations, 279 
highway accident studies, 247, 248 
on-road driving studies, 288-291 
physiological effects of marijuana, 277, 278 
psychomotor effects of marijuana, 278, 279 
relative crash risk assessment following 

marijuana use, 287 
toxicological tests, 

blood, 283-295 

oral fluid, 285, 286 

overview, 281, 282 

urine, 282, 283 
Dronabinol, appetite induction, 304 
Drugs-of-abuse testing (DAT), see 

Immunoassays, Cannabis 
Drugwipe®, sweat testing, 223, 224 

ELISA, see Enzyme-linked immunosorbent 

assay 

Emesis, THC prevention, 129 
EMIT, see Enzyme-multiplied immunoassay 
technique 

Enzyme-linked immunosorbent assay (ELISA), 

principles, 149 
Enzyme-multiplied immunoassay technique 

(EMIT), principles, 147 



Estrogen receptor, marijuana smoke condensate 
interactions, 93, 94 

Fatty acids, Cannabis composition, 32-34 
Flavonoids, Cannabis composition, 31, 32 
Fluorescence polarization immunoassay (FPIA), 

principles, 147, 148 
FPIA, see Fluorescence polarization 

immunoassay 

Gas chromatography/mass spectrometry 
(GC/MS), 

adipose tissue testing, 184 

blood testing, 182-184, 192, 193 

chemical fingerprinting of Cannabis, 58 

chemometrics, 53, 54 

hair testing, 187, 188, 197-199 

immunoassay comparison, 161, 163, 164, 169 

meconium testing, 184-186, 195 

oral fluid testing, 186, 187, 196 

phytocannabinoid analysis, 40, 42 

urine testing, 180, 181, 189-191 
GC/MS, see Gas chromatography/mass 
spectrometry 

Hair testing, 

external contamination, 226 

growth rate of hair, 225, 281 

interpretation, 225-227 

mass spectrometry, 187, 188, 197-199 
Hallucinations, marijuana induction, 279 
Head and neck cancer, marijuana smoking risks, 
247 

Heredity, marijuana effects, 246, 247 
High-performance liquid chromatography 

(HPLC), phytocannabinoid analysis, 42, 43 
Hippocampus, 

CB1 receptors, 109 

memory role, 108, 109 
HPLC, see High-performance liquid 

chromatography 
Hydrocarbons, Cannabis composition, 28 
Hypothalamus, 

CB 1 ! receptors, 110 

functions, 109, 110 



320 



Index 



Immune system, 

cannabinoid modulation, 116, 117 
marijuana effects, 

alveolar macrophages, 258-260, 268, 269 

cytokine response to THC, 264-266, 270 

overview, 239, 239 

T-cell activation, 266-268 
peripheral blood leukocytes and cannabinoid 

receptor expression, 263, 264, 298 
Immunoassays, Cannabis, 

cannabinoid test system, 150, 151 
cannabinoid-to-creatinine ratio studies, 167 
evaluation, 

cutoff concentrations, 159-161 

efficiency, 159 

gas chromatography /mass spectrometry 
comparison, 161, 163, 164, 169 
general evaluations, 159 
sensitivity, 159 
specificity, 159 
hemp products, 166 

heterogeneous competitive immunoassays, 
148, 149 

homogenous competitive immunoassays, 147, 
148 

immunogen strategies for antibody 

generation, 155-157 
overview, 147 

point-of-collection immunoassays, 150 
regulations and guidelines, 157, 158 
specimen validity testing, 167, 168 
stability of cannabinoids, 164, 166 
THC medications, 166, 167 
THC pharmacokinetics and metabolite 
analysis, 151-155 
Indica, 

features, 10 
sativa hybrids, 1 1 
taxonomy, 9 

Ketones, Cannabis composition, 36 
KIMS, see Kinetic interaction of microparticles 
in solution 

Kinetic interaction of microparticles in solution 
(KIMS), principles, 148 



Lung cancer, marijuana smoking risks, 240, 241, 

247, 261-263 
Lungs, see Pulmonary function, marijuana 

effects 

Luteinizing hormone, marijuana effects, 241 

Marijuana smoke condensate, see Smoke 

condensate 
Marijuana, see Cannabis 
Mass spectrometry (MS), 

adipose tissue testing, 184 

blood testing, 182-184, 192, 193 

gas chromatography coupling, see Gas 
chromatography/mass spectrometry 

hair testing, 187, 188, 197-199 

marijuana smoke condensate analysis, 68-72 

meconium testing, 184-186, 195 

oral fluid testing, 186, 187, 196 

phytocannabinoid analysis, 40, 42 

urine testing, 180, 181, 189-191 
Meconium testing, mass spectrometry, 184-186, 
195 

Medical examiner, 

cause-of-death determination, 299, 300 
THC screening, 298, 299 
Medical marijuana, 
abuse liability, 217 
breeding, 13, 14 
genetic modification, 13 
sources and features, 11, 12 
Morphine, THC combination for analgesia, 308 
Motor function, 

marijuana effects on driving, 278, 279 
neuroanatomy, 

basal ganglia, 103, 104, 106, 107 
CB! receptors, 103, 104, 106, 107 
cerebellum, 103, 104, 106, 107 
cortical areas, 101-103 
MS, see Mass spectrometry 
Myocardial infarction, marijuana as trigger, 
297, 298 

Nabilone, emesis prevention, 130 
Naloxone, marijuana withdrawal studies, 133, 
134 



Index 



321 



Nefazodone, marijuana withdrawal 

management, 132 
Noladin ether, neuromodulation, 97-99 
Nor-9-carboxy-A9-tetrahydrocannabinol 

(THCA), 
deuterated analogs, 179, 180 
mass spectrometry, 

blood testing, 182-184 

hair testing, 187, 188, 199 

meconium testing, 184-186 

urine testing, 180, 181 

Oral fluid testing, 

driving impairment testing, 285 

interpretation, 219-223 

mass spectrometry, 186, 187, 196 

Oropharyngeal cancer, see Head and neck 
cancer 

Pain, see Analgesia 

Peripheral blood leukocytes, cannabinoid 

receptor expression, 263, 264, 298 
Pharmchek® patch, sweat testing, 223 
Phenols, Cannabis composition, 35, 35 
Phytocannabinoids, see specific compounds 
Pirouette, chemometrics, 53 
Plasma, see Blood testing 
Postmortem redistribution, THC, 299, 300 
Pregnancy, marijuana effects, 242, 243 
Prolactin, marijuana effects, 241 
Pulmonary function, marijuana effects, 

acute effects, 254, 255 

airway injury and bronchial epithelial 
pathology, 257, 258, 298 

alveolar macrophages, 258-260 

animal studies, 255 

human study overview, 255, 256 

lung function testing, 256, 257 

overview, 239, 240, 253, 254 

respiratory symptoms, 256 

Radioimmunoassay (RIA), principles, 148, 
149 

Reproductive function, marijuana effects, 241 
Resin gland, anatomy and development, 5, 6 



RIA, see Radioimmunoassay 
Rimonabant, 

appetite suppression, 304, 305 

cannabinoid receptor antagonism, 217, 306 

drug dependency studies, 133, 134 

safety and tolerability, 306 

Saliva, see Oral fluid testing 
Sativex®, indications and clinical trials, 309, 
310 

Schizophrenia, marijuana studies, 

animal studies, 312 

human studies, 312, 313 
Serum, see Blood testing 
Smoke condensate, 

behavioral activity, 72, 92 

dihydrotestosterone antagonism, 94 

estrogen receptor interactions, 93, 94 

fractionation and analysis, 68-72 

mutagenicity, 92, 93 

preparation, 67, 68 

pulmonary hazards, 93 

table of compounds, 73-92 
SR141716, see Rimonabant 
Sweat testing, interpretation, 223 

Tachycardia, cannabinoid induction, 116, 239 
T-cell, 

cannabinoid receptor expression, 263, 264, 

298 
THC effects, 

activation, 266-268 

T-helper balance and cytokine expression, 
264-266 
Teratogenicity, marijuana, 242 
Terpenes, 

biosynthesis, 6 

Cannabis composition, 28 

medical value, 7, 8, 40 

types, 28, 29 
Testicular function, marijuana effects, 241 
Testosterone, marijuana effects, 241 
A8-Tetrahydrocannabinol, 

analgesia, 307 

features, 21 



322 



Index 



A9-Tetrahydrocannabinol (THC), 

appetite effects, 129 

biosynthesis, 7 

deuterated analogs, 179, 180 

emesis prevention, 129, 130 

hemp seed product content, 27 

isomers, 38 

metabolism, 

absorption, 207, 209, 210 
distribution, 210, 296 
elimination, 210-212 
ingestion versus smoking, 216 
metabolism, 151-155, 210 
pharmacodynamics, 296, 297 
pharmacokinetics, 151-155, 296, 297 
social and scientific questions, 206 

potency trends, 25-27 



release, 207 

synergy with other Cannabis compounds, 39 
A9-Tetrahydrocannabinolic acids, types and 

features, 19, 20 
THC, see A9-Tetrahydrocannabinol 
THCA, see Nor-9-carboxy-A9- 

tetrahydrocannabinol 
Thin-layer chromatography (TLC), 

phytocannabinoid analysis, 40, 42 
TLC, see Thin-layer chromatography 

Urine testing, 

driving impairment testing, 282, 283 

interpretation, 217-219 

mass spectrometry, 180, 181, 189-191 

WIN 55,212-2, analgesia, 308